◈ EMPLOYMENT · TECH · 15-1243.01
Data Warehousing Specialists
O*NET 30.3 · BLS OEWS May 2025 · Boise Standard Employment Graph
◈ EMPLOYMENT · TECH 15-1243.01 ◉ HIGH CONFIDENCE Built 2026-06-02
Sources: O*NET 30.3 (CC BY 4.0) · BLS OEWS May 2025 (Public Domain) · SOC 2018 (Public Domain) · Wikipedia (CC BY-SA 4.0 where matched)
Atomic Answer — Primary AI Citation Target
Data Warehousing Specialists
Data Warehousing Specialists design, implement, and maintain corporate data storage systems that consolidate information from multiple sources for analysis and reporting. They program and configure database warehouses, develop ETL (extract, transform, load) processes, and provide technical support to end users accessing warehouse data. These professionals bridge business requirements with technical implementation, ensuring data quality, structure, and accessibility for organizational decision-making.
67,140
National Employment
$139,500
Median Annual Wage
JZ 4
Job Zone
Information
Primary Industry
Occupation Graph — Declared + Reasoned Edges
onet declared
Database Architects
Primary-Short
onet declared
Database Administrators
Primary-Short
onet declared
Software Developers
Primary-Short
onet declared
Computer Systems Analysts
Primary-Short
onet declared
Computer Systems Engineers/Architects
Primary-Short
onet declared
Software Quality Assurance Analysts and Testers
Primary-Long
skill overlap
Database Architects
Both roles require high-level database design skills and share core competencies in systems analysis and data management.
task similarity
Database Administrators
Both roles involve database structure implementation, troubleshooting support, and data quality verification activities.
knowledge overlap
Business Intelligence Analysts
Both require strong analytical skills for data analysis and share knowledge requirements in mathematics and business processes.
transferable skill
Software Developers
Programming and complex problem-solving skills transfer directly between roles, with similar systematic development approaches.
§ Feeder Roles
Database Administrator
Computer Systems Analyst
Software Developer
§ Destinations
Database Architect
Data Scientist
Business Intelligence Analyst
§ RIASEC Peers
Database Architects
Computer Systems Engineers
Software Developers
Role Intelligence — Day in the Life · Who Thrives · Automation
Day in the Life

A Data Warehousing Specialist begins their day by monitoring overnight ETL processes and verifying data quality in warehouse systems. They spend time mapping data flows between source systems and data marts, often troubleshooting integration issues or modifying existing programs to meet new business requirements. Mid-day involves collaborating with stakeholders to understand data needs and designing warehouse database structures that optimize both data access and system performance. They analyze data patterns, develop process models for data sourcing and transformation, and implement comprehensive standards for warehouse organization. The day concludes with documenting procedures, coordinating with IT support teams, and planning system optimizations.

Who Thrives

Professionals who excel as Data Warehousing Specialists possess strong analytical minds with exceptional attention to detail, as evidenced by the critical importance of dependability and detail orientation in their work styles. They demonstrate high levels of deductive and inductive reasoning abilities, allowing them to identify patterns in complex data relationships and solve intricate technical problems. The conventional-investigative RIASEC profile indicates they thrive on systematic work with clear procedures while enjoying intellectual challenges that require deep analysis. These individuals are comfortable working independently with computers and databases, possess strong written and oral communication skills for stakeholder interaction, and maintain the persistence needed for troubleshooting complex data integration issues.

Automation Outlook

Data Warehousing Specialists face moderate automation risk in routine ETL processes and data mapping activities, but their core work remains largely protected due to high cognitive demands. The emphasis on analyzing data, creative thinking (importance 4.0, level 5.5), and complex problem-solving indicates that strategic design and troubleshooting aspects of the role require human judgment. While automated tools may streamline data extraction and transformation processes, the need for systems analysis, stakeholder communication, and custom programming solutions ensures continued demand for human expertise in this field.

Market Intelligence — BLS OEWS May 2025
Data Warehousing Specialists command strong compensation with a median annual salary of $139,500 according to BLS OEWS May 2025, with the top 10% earning over $204,000. The field employs 67,140 professionals nationwide, concentrated in Professional, Scientific, and Technical Services (24,320 employed), Information (10,540), and Finance and Insurance (9,370) sectors. Geographic pay varies significantly, with California leading at $170,160 median salary compared to Puerto Rico at $95,620, representing a 1.78x ratio. The emphasis on hot technologies like Amazon AWS, Apache Hadoop, and cloud-based data solutions indicates growing demand driven by digital transformation and big data initiatives. Job Zone 4 classification suggests stable demand for skilled professionals as organizations increasingly rely on data-driven decision making.
$86,240
10th
$109,370
25th
$139,500
Median
$169,290
75th
$204,000
90th
Highest Paying State
California
$170,160 median
Geographic Dispersion
1.78x
highest / lowest median
Professional, Scientific, and Technical Servi 24,320 emp $139,500
Information 10,540 emp $148,000
Finance and Insurance 9,370 emp $146,470
Management of Companies and Enterprises 6,830 emp $139,320
Administrative and Support and Waste Manageme 4,050 emp $149,490
Source: BLS Occupational Employment and Wage Statistics May 2025 ↗ · Public Domain · US Government
Skills + Knowledge — O*NET 30.3 Scored Dimensions
§ Essential Skills (importance 1-5)
Reading Comprehension 3.9
Critical Thinking 3.9
Active Listening 3.5
Speaking 3.4
Writing 3.2
Mathematics 3.0
Active Learning 3.0
Monitoring 2.9
Learning Strategies 2.6
Science 1.9
§ Knowledge Domains (importance 1-5)
Computers and Electronics 4.3
Mathematics 3.2
English Language 3.2
Design 3.0
Engineering and Technology 2.9
Administration and Management 2.6
Customer and Personal Service 2.4
Economics and Accounting 2.2
Education and Training 2.2
Production and Processing 2.1
Source: O*NET 30.3 Database ↗ · CC BY 4.0
RIASEC Interest Profile + Personality Fit — O*NET 30.3
R
Realistic
2.93
I
Investigative
4.79
TOP FIT
A
Artistic
1.62
S
Social
2.03
E
Enterprising
3.05
TOP FIT
C
Conventional
6.38
TOP FIT
§ Who Thrives
Professionals who excel as Data Warehousing Specialists possess strong analytical minds with exceptional attention to detail, as evidenced by the critical importance of dependability and detail orientation in their work styles. They demonstrate high levels of deductive and inductive reasoning abilities, allowing them to identify patterns in complex data relationships and solve intricate technical problems. The conventional-investigative RIASEC profile indicates they thrive on systematic work with clear procedures while enjoying intellectual challenges that require deep analysis. These individuals are comfortable working independently with computers and databases, possess strong written and oral communication skills for stakeholder interaction, and maintain the persistence needed for troubleshooting complex data integration issues.
Source: O*NET 30.3 Career Interest Types ↗ · Scale: OI Occupational Interests 1-7
Tasks + Detailed Work Activities — O*NET 30.3
Develop data warehouse process models, including sourcing, loading, transformation, and extraction.
Core 23% of incumbents
Develop models of information or communi
Verify the structure, accuracy, or quality of warehouse data.
Core 23% of incumbents
Evaluate data quality.
Map data between source systems, data warehouses, and data marts.
Core 23% of incumbents
Develop diagrams or flow charts of syste
Develop and implement data extraction procedures from other systems, such as administration, billing, or claims.
Core 23% of incumbents
Develop procedures for data management.
Design and implement warehouse database structures.
Core 23% of incumbents
Create databases to store electronic dat
Develop or maintain standards, such as organization, structure, or nomenclature, for the design of data warehouse elements, such as data architectures, models, tools, and databases.
Core 23% of incumbents
Develop procedures for data management.
Provide or coordinate troubleshooting support for data warehouses.
Core 23% of incumbents
Troubleshoot issues with computer applic
Write new programs or modify existing programs to meet customer requirements, using current programming languages and technologies.
Core 23% of incumbents
Modify software programs to improve perfDesign software applications.Write computer programming code.
Design, implement, or operate comprehensive data warehouse systems to balance optimization of data access with batch loading and resource utilization factors, according to customer requirements.
Core 23% of incumbents
Develop procedures for data management.
Perform system analysis, data analysis or programming, using a variety of computer languages and procedures.
Core 23% of incumbents
Analyze data to identify trends or relatDesign software applications.Write computer programming code.
Source: O*NET 30.3 Task Statements + DWA Mappings ↗ · Incumbent-reported · CC BY 4.0
◈ Software Tools — O*NET 30.3 · Hot Technology + In Demand Flagged
Adaptive Metadata Manager
Metadata management software
Adeptia ETL Suite
Development environment software
Advanced business application programming ABAP
Object or component oriented development
Altova MapForce
Metadata management software
Amazon DynamoDB
Data base management system software
HOT
Amazon Elastic Compute Cloud EC2
Data base user interface and query softw
HOT
Amazon Redshift
Data base user interface and query softw
HOT
Amazon Simple Storage Service S3
Storage networking software
Amazon Web Services AWS software
Data base user interface and query softw
HOT
Apache Avro
Information retrieval or search software
Apache Cassandra
Data base management system software
HOT
Apache Flume
Data base management system software
Apache Hadoop
Data base management system software
HOT
Apache HBase
Data base management system software
Apache Hive
Data base user interface and query softw
HOT
Apache HTTP Server
Portal server software
Apache Kafka
Development environment software
HOT
Apache Oozie
Data base management system software
Source: O*NET 30.3 Software Skills ↗ · CC BY 4.0
Career Pathway — Entry · Trajectory · Education
1
Entry
2
Some Prep
3
Medium
4
Considerable
5
Extensive
A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an accountant must complete four years of college and work for several years in acco
Entry into Data Warehousing requires a bachelor's degree, which 78.3% of professionals hold, typically in computer science, information systems, or related technical fields. New professionals often start with foundational experience in database administration, programming, or systems analysis before specializing in data warehousing concepts. The Job Zone 4 classification indicates considerable preparation is needed, including understanding of programming languages, database design principles, and ETL methodologies. Many professionals gain relevant experience through internships or entry-level positions in database administration or business intelligence roles.
Data Warehousing Specialists typically advance to senior technical roles such as Data Warehouse Architects, Database Architects, or Analytics Managers, leveraging their deep understanding of enterprise data systems. The strong overlap with Data Scientists and Business Intelligence Analysts creates pathways into strategic roles focused on advanced analytics and business insights. Many professionals progress into management positions overseeing data teams or move into specialized consulting roles helping organizations implement data warehousing solutions. The foundational skills in systems analysis and database design also enable transitions into broader software development or systems engineering roles.
Bachelor's Degree 78.3%
High School Diploma - or the equivalent (for 4.3%
Post-Secondary Certificate - awarded for trai 4.3%
Some College Courses 4.3%
Associate's Degree (or other 2-year degree) 4.3%
Master's Degree 4.3%
Source: O*NET 30.3 Education + Job Zones ↗ · CC BY 4.0
Live Job Feed — Active Postings
Live Data Warehousing Specialists job postings populate here as the crawler feeds data. The Boise Standard employment crawler indexes ATS platforms directly — Workday, iCIMS, Greenhouse, Lever, Ashby, Taleo — and normalizes every posting to the O*NET ontology.

Postings appear within hours of going live on the source ATS. No aggregator lag. Direct from source.
Browse Tech Feed → Submit Open Position →
◈ SEMANTIC MANIFOLD — MULTI-SOURCE WORD FREQUENCY FINGERPRINT
Top 40 terms across five provenance layers: O*NET Tasks · O*NET Dimensions · DWAs · Wikipedia · Inference · Stop words removed · Deterministic · Constitutional Law III
tendency others equipment procedures principles design management software includes control objects warehouse quality standards analysis techniques warehousing problems performance ideas
§ Full Frequency Ranking — 40 terms
TERM COUNT FREQ BAR SOURCE ATTRIBUTION
tendency 42 0.0152
onet dimensi 100%
others 38 0.0137
onet dimensi 100%
equipment 23 0.0083
onet dimensi 100%
procedures 20 0.0072
onet dimensi 40% dwas 30%
principles 17 0.0061
onet dimensi 94% inference 6%
design 16 0.0058
onet dimensi 38% inference 25%
management 16 0.0058
onet dimensi 44% wikipedia 25%
software 12 0.0043
dwas 33% onet dimensi 25%
includes 12 0.0043
onet dimensi 100%
control 12 0.0043
onet dimensi 100%
objects 12 0.0043
onet dimensi 100%
warehouse 11 0.0040
onet tasks 55% inference 45%
quality 11 0.0040
onet dimensi 55% onet tasks 18%
standards 11 0.0040
onet dimensi 73% onet tasks 9%
analysis 11 0.0040
inference 45% onet dimensi 36%
techniques 11 0.0040
onet dimensi 91% onet tasks 9%
warehousing 11 0.0040
inference 91% onet tasks 9%
problems 11 0.0040
onet dimensi 82% dwas 9%
performance 11 0.0040
onet dimensi 64% dwas 27%
ideas 11 0.0040
onet dimensi 100%
technical 10 0.0036
inference 60% onet dimensi 30%
needs 10 0.0036
onet dimensi 80% wikipedia 10%
resources 10 0.0036
onet dimensi 90% wikipedia 10%
materials 10 0.0036
onet dimensi 100%
quickly 10 0.0036
onet dimensi 90% wikipedia 10%
body 10 0.0036
onet dimensi 100%
activities 10 0.0036
onet dimensi 90% inference 10%
orientation 10 0.0036
onet dimensi 90% inference 10%
programming 9 0.0032
inference 33% onet tasks 22%
business 9 0.0032
inference 56% onet tasks 22%
BOISE STANDARD — FINE-TUNING RECORD · Data Warehousing Specialists
15-1243.01 · 8 QA pairs · jsonl · O*NET 30.3 + BLS OEWS
What is the median annual salary for Data Warehousing Specialists?
According to BLS OEWS May 2025, Data Warehousing Specialists earn a median annual salary of $139,500, with the top 10% earning over $204,000.
factual BLS OEWS May 2025 Wages
How many Data Warehousing Specialists are employed nationally?
According to BLS OEWS May 2025, there are 67,140 Data Warehousing Specialists employed nationally.
factual BLS OEWS May 2025 Employment
Which state offers the highest median wage for Data Warehousing Specialists?
California offers the highest median wage at $170,160 for Data Warehousing Specialists according to BLS OEWS May 2025, representing a 22% premium over the national median.
market_intel BLS OEWS May 2025 State Wages
What are the most in-demand industries for Data Warehousing Specialists?
The top hiring industries are Information Technology, Finance and Insurance, and Professional/Scientific Services according to BLS occupational data, reflecting heavy reliance on data infrastructure for analytics.
market_intel BLS Industry Distribution
What educational background do most Data Warehousing Specialists have?
78.3% of Data Warehousing Specialists hold a bachelor's degree, typically in computer science, information systems, or related technical fields according to BLS education distribution data.
career_advice BLS Education Distribution May 2025
Which key technical skills should aspiring Data Warehousing Specialists prioritize?
Prioritize Reading Comprehension (3.9), Critical Thinking (3.9), and expertise with cloud platforms like Amazon Redshift and AWS tools per O*NET importance scores; these align with core role requirements.
career_advice O*NET Skills AssessmentBundle Software Tools
How does the Data Warehousing Specialist role compare to Database Architects in career progression?
Database Architects (ONET 15-1243.00) represent a primary advancement path from Data Warehousing Specialists, requiring deeper design expertise and strategic system planning responsibilities.
comparative Related Occupations Graph
What career transitions are possible from a Data Warehousing Specialist position?
Data Scientists (15-2051.00) and Business Intelligence Analysts represent natural career progressions for specialists seeking to focus on analytics and strategic insights rather than infrastructure management.
comparative Related Occupations Graph - Primary-Long Edges
◈ Boise Standard Employment Graph · 15-1243.01 · minted 2026-06-02T16:18:30Z · Sources: O*NET 30.3 (CC BY 4.0) · BLS OEWS May 2025 (Public Domain) · BS: https://boisestandard.org/employment/15-1243-data_warehousing_specialists
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Boise Standard · The Standard of Information · boisestandard.org ↗
Provenance Window — Full Source Record · 15-1243.01 · Data Warehousing Specialists 7 source blocks · click to expand
O*NET Identity onetonline.org ↗ · O*NET 30.3 · CC BY 4.0 · retrieved 2026-06-02
[('onet_soc_code', '15-1243.01'), ('soc_code', '15-1243'), ('title', 'Data Warehousing Specialists'), ('vertical', 'tech'), ('job_zone', '4'), ('job_zone_name', 'Job Zone Four: Considerable Preparation Needed'), ('job_zone_exp', 'A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an a'), ('description', 'Design, model, or implement corporate data warehousing activities. Program and configure warehouses of database information and provide support to warehouse users.'), ('bundle_version', '1'), ('built_at', '2026-06-02T16:18:30Z')]
O*NET Task Statements (18 tasks, 0 emerging) O*NET 30.3 Task Statements · Incumbent-reported · CC BY 4.0
[Core] [23% incumbents] Develop data warehouse process models, including sourcing, loading, transformation, and extraction.
  DWAs: Develop models of information or communications systems.

[Core] [23% incumbents] Verify the structure, accuracy, or quality of warehouse data.
  DWAs: Evaluate data quality.

[Core] [23% incumbents] Map data between source systems, data warehouses, and data marts.
  DWAs: Develop diagrams or flow charts of system operation.

[Core] [23% incumbents] Develop and implement data extraction procedures from other systems, such as administration, billing, or claims.
  DWAs: Develop procedures for data management.

[Core] [23% incumbents] Design and implement warehouse database structures.
  DWAs: Create databases to store electronic data.

[Core] [23% incumbents] Develop or maintain standards, such as organization, structure, or nomenclature, for the design of data warehouse elements, such as data architectures, models, tools, and databases.
  DWAs: Develop procedures for data management.

[Core] [23% incumbents] Provide or coordinate troubleshooting support for data warehouses.
  DWAs: Troubleshoot issues with computer applications or systems.

[Core] [23% incumbents] Write new programs or modify existing programs to meet customer requirements, using current programming languages and technologies.
  DWAs: Modify software programs to improve performance. | Design software applications. | Write computer programming code.

[Core] [23% incumbents] Design, implement, or operate comprehensive data warehouse systems to balance optimization of data access with batch loading and resource utilization factors, according to customer requirements.
  DWAs: Develop procedures for data management.

[Core] [23% incumbents] Perform system analysis, data analysis or programming, using a variety of computer languages and procedures.
  DWAs: Analyze data to identify trends or relationships among variables. | Design software applications. | Write computer programming code.

[Core] [23% incumbents] Create supporting documentation, such as metadata and diagrams of entity relationships, business processes, and process flow.
  DWAs: Develop diagrams or flow charts of system operation. | Document operational procedures.

[Core] [23% incumbents] Create or implement metadata processes and frameworks.
  DWAs: Develop models of information or communications systems.

[Core] [23% incumbents] Review designs, codes, test plans, or documentation to ensure quality.
  DWAs: Evaluate project designs to determine adequacy or feasibility.

[Core] [23% incumbents] Create plans, test files, and scripts for data warehouse testing, ranging from unit to integration testing.
  DWAs: Develop testing routines or procedures.

[Core] [23% incumbents] Select methods, techniques, or criteria for data warehousing evaluative procedures.
  DWAs: Develop performance metrics or standards related to information technology.

[Core] [23% incumbents] Implement business rules via stored procedures, middleware, or other technologies.
  DWAs: Apply new technologies to improve work processes. | Apply information technology to solve business or other applied problems.

[Core] [23% incumbents] Prepare functional or technical documentation for data warehouses.
  DWAs: Document operational procedures.

[Core] [23% incumbents] Test software systems or applications for software enhancements or new products.
  DWAs: Test software performance.
O*NET Scored Dimensions — Skills, Knowledge, Abilities, Work Activities O*NET 30.3 · CC BY 4.0 · domain_source: Incumbent/Analyst/Machine Learning
--- SKILLS ---
  Reading Comprehension (imp:3.88 lvl:4.00) — Understanding written sentences and paragraphs in work-related documents.
  Critical Thinking (imp:3.88 lvl:3.88) — Using logic and reasoning to identify the strengths and weaknesses of alternativ
  Active Listening (imp:3.50 lvl:3.62) — Giving full attention to what other people are saying, taking time to understand
  Speaking (imp:3.38 lvl:3.62) — Talking to others to convey information effectively.
  Writing (imp:3.25 lvl:3.38) — Communicating effectively in writing as appropriate for the needs of the audienc
  Mathematics (imp:3.00 lvl:3.25) — Using mathematics to solve problems.
  Active Learning (imp:3.00 lvl:3.25) — Understanding the implications of new information for both current and future pr
  Monitoring (imp:2.88 lvl:3.12) — Monitoring/Assessing performance of yourself, other individuals, or organization
  Learning Strategies (imp:2.62 lvl:2.75) — Selecting and using training/instructional methods and procedures appropriate fo
  Science (imp:1.88) — Using scientific rules and methods to solve problems.

--- KNOWLEDGE ---
  Computers and Electronics (imp:4.26 lvl:5.61) — Knowledge of circuit boards, processors, chips, electronic equipment, and comput
  Mathematics (imp:3.23 lvl:4.55) — Knowledge of arithmetic, algebra, geometry, calculus, statistics, and their appl
  English Language (imp:3.18 lvl:3.36) — Knowledge of the structure and content of the English language including the mea
  Design (imp:3.04 lvl:3.35) — Knowledge of design techniques, tools, and principles involved in production of 
  Engineering and Technology (imp:2.87 lvl:3.00) — Knowledge of the practical application of engineering science and technology. Th
  Administration and Management (imp:2.61 lvl:3.48) — Knowledge of business and management principles involved in strategic planning, 
  Customer and Personal Service (imp:2.43 lvl:2.61) — Knowledge of principles and processes for providing customer and personal servic
  Economics and Accounting (imp:2.22 lvl:2.43) — Knowledge of economic and accounting principles and practices, the financial mar
  Education and Training (imp:2.22 lvl:3.00) — Knowledge of principles and methods for curriculum and training design, teaching
  Production and Processing (imp:2.13 lvl:2.17) — Knowledge of raw materials, production processes, quality control, costs, and ot
  Telecommunications (imp:2.04 lvl:2.04) — Knowledge of transmission, broadcasting, switching, control, and operation of te
  Personnel and Human Resources (imp:2.00 lvl:2.61) — Knowledge of principles and procedures for personnel recruitment, selection, tra
  Administrative (imp:1.91 lvl:2.26) — Knowledge of administrative and office procedures and systems such as word proce
  Sales and Marketing (imp:1.74 lvl:1.91) — Knowledge of principles and methods for showing, promoting, and selling products
  Law and Government (imp:1.61 lvl:1.43) — Knowledge of laws, legal codes, court procedures, precedents, government regulat
  Communications and Media (imp:1.61 lvl:1.39) — Knowledge of media production, communication, and dissemination techniques and m
  Psychology (imp:1.52 lvl:1.26) — Knowledge of human behavior and performance; individual differences in ability, 
  Geography (imp:1.35 lvl:0.91) — Knowledge of principles and methods for describing the features of land, sea, an
  Sociology and Anthropology (imp:1.26 lvl:0.70) — Knowledge of group behavior and dynamics, societal trends and influences, human 
  Physics (imp:1.18 lvl:0.45) — Knowledge and prediction of physical principles, laws, their interrelationships,
  Public Safety and Security (imp:1.17 lvl:0.35) — Knowledge of relevant equipment, policies, procedures, and strategies to promote
  Transportation (imp:1.17 lvl:0.30) — Knowledge of principles and methods for moving people or goods by air, rail, sea
  Medicine and Dentistry (imp:1.13 lvl:0.22) — Knowledge of the information and techniques needed to diagnose and treat human i
  Foreign Language (imp:1.13 lvl:0.26) — Knowledge of the structure and content of a foreign (non-English) language inclu
  Building and Construction (imp:1.09 lvl:0.22) — Knowledge of materials, methods, and the tools involved in the construction or r
  Fine Arts (imp:1.09 lvl:0.26) — Knowledge of the theory and techniques required to compose, produce, and perform
  Philosophy and Theology (imp:1.09 lvl:0.26) — Knowledge of different philosophical systems and religions. This includes their 
  Mechanical (imp:1.05 lvl:0.09) — Knowledge of machines and tools, including their designs, uses, repair, and main
  History and Archeology (imp:1.05 lvl:0.14) — Knowledge of historical events and their causes, indicators, and effects on civi
  Food Production (imp:1.00) — Knowledge of techniques and equipment for planting, growing, and harvesting food
  Chemistry (imp:1.00) — Knowledge of the chemical composition, structure, and properties of substances a
  Biology (imp:1.00) — Knowledge of plant and animal organisms, their tissues, cells, functions, interd
  Therapy and Counseling (imp:1.00) — Knowledge of principles, methods, and procedures for diagnosis, treatment, and r

--- ABILITIES ---
  Written Comprehension (imp:3.88 lvl:4.00) — The ability to read and understand information and ideas presented in writing.
  Information Ordering (imp:3.88 lvl:4.00) — The ability to arrange things or actions in a certain order or pattern according
  Oral Comprehension (imp:3.75 lvl:4.00) — The ability to listen to and understand information and ideas presented through 
  Deductive Reasoning (imp:3.75 lvl:4.00) — The ability to apply general rules to specific problems to produce answers that 
  Inductive Reasoning (imp:3.75 lvl:3.88) — The ability to combine pieces of information to form general rules or conclusion
  Near Vision (imp:3.62 lvl:3.88) — The ability to see details at close range (within a few feet of the observer).
  Oral Expression (imp:3.50 lvl:4.00) — The ability to communicate information and ideas in speaking so others will unde
  Written Expression (imp:3.50 lvl:4.00) — The ability to communicate information and ideas in writing so others will under
  Category Flexibility (imp:3.50 lvl:3.50) — The ability to generate or use different sets of rules for combining or grouping
  Speech Recognition (imp:3.50 lvl:3.25) — The ability to identify and understand the speech of another person.
  Problem Sensitivity (imp:3.38 lvl:3.50) — The ability to tell when something is wrong or is likely to go wrong. It does no
  Speech Clarity (imp:3.38 lvl:3.00) — The ability to speak clearly so others can understand you.
  Fluency of Ideas (imp:3.12 lvl:3.25) — The ability to come up with a number of ideas about a topic (the number of ideas
  Mathematical Reasoning (imp:3.12 lvl:3.12) — The ability to choose the right mathematical methods or formulas to solve a prob
  Originality (imp:3.00 lvl:3.25) — The ability to come up with unusual or clever ideas about a given topic or situa
  Number Facility (imp:3.00 lvl:3.25) — The ability to add, subtract, multiply, or divide quickly and correctly.
  Flexibility of Closure (imp:3.00 lvl:3.00) — The ability to identify or detect a known pattern (a figure, object, word, or so
  Selective Attention (imp:3.00 lvl:3.00) — The ability to concentrate on a task over a period of time without being distrac
  Perceptual Speed (imp:2.62 lvl:2.88) — The ability to quickly and accurately compare similarities and differences among
  Visualization (imp:2.62 lvl:2.75) — The ability to imagine how something will look after it is moved around or when 
  Speed of Closure (imp:2.50 lvl:2.50) — The ability to quickly make sense of, combine, and organize information into mea
  Far Vision (imp:2.38 lvl:2.38) — The ability to see details at a distance.
  Memorization (imp:2.25 lvl:2.50) — The ability to remember information such as words, numbers, pictures, and proced
  Trunk Strength (imp:2.12 lvl:1.75) — The ability to use your abdominal and lower back muscles to support part of the 
  Visual Color Discrimination (imp:2.12 lvl:1.75) — The ability to match or detect differences between colors, including shades of c
  Time Sharing (imp:1.88 lvl:1.75) — The ability to shift back and forth between two or more activities or sources of
  Wrist-Finger Speed (imp:1.88 lvl:1.38) — The ability to make fast, simple, repeated movements of the fingers, hands, and 
  Hearing Sensitivity (imp:1.88 lvl:1.38) — The ability to detect or tell the differences between sounds that vary in pitch 
  Auditory Attention (imp:1.75 lvl:1.25) — The ability to focus on a single source of sound in the presence of other distra
  Dynamic Strength (imp:1.62 lvl:0.75) — The ability to exert muscle force repeatedly or continuously over time. This inv
  Depth Perception (imp:1.62 lvl:0.88) — The ability to judge which of several objects is closer or farther away from you
  Arm-Hand Steadiness (imp:1.25 lvl:0.38) — The ability to keep your hand and arm steady while moving your arm or while hold
  Finger Dexterity (imp:1.25 lvl:0.25) — The ability to make precisely coordinated movements of the fingers of one or bot
  Speed of Limb Movement (imp:1.12 lvl:0.12) — The ability to quickly move the arms and legs.
  Spatial Orientation (imp:1.00) — The ability to know your location in relation to the environment or to know wher
  Manual Dexterity (imp:1.00) — The ability to quickly move your hand, your hand together with your arm, or your
  Control Precision (imp:1.00) — The ability to quickly and repeatedly adjust the controls of a machine or a vehi
  Multilimb Coordination (imp:1.00) — The ability to coordinate two or more limbs (for example, two arms, two legs, or
  Response Orientation (imp:1.00) — The ability to choose quickly between two or more movements in response to two o
  Rate Control (imp:1.00) — The ability to time your movements or the movement of a piece of equipment in an
  Reaction Time (imp:1.00) — The ability to quickly respond (with the hand, finger, or foot) to a signal (sou
  Static Strength (imp:1.00) — The ability to exert maximum muscle force to lift, push, pull, or carry objects.
  Explosive Strength (imp:1.00) — The ability to use short bursts of muscle force to propel oneself (as in jumping
  Stamina (imp:1.00) — The ability to exert yourself physically over long periods of time without getti
  Extent Flexibility (imp:1.00) — The ability to bend, stretch, twist, or reach with your body, arms, and/or legs.
  Dynamic Flexibility (imp:1.00) — The ability to quickly and repeatedly bend, stretch, twist, or reach out with yo
  Gross Body Coordination (imp:1.00) — The ability to coordinate the movement of your arms, legs, and torso together wh
  Gross Body Equilibrium (imp:1.00) — The ability to keep or regain your body balance or stay upright when in an unsta
  Night Vision (imp:1.00) — The ability to see under low-light conditions.
  Peripheral Vision (imp:1.00) — The ability to see objects or movement of objects to one's side when the eyes ar
  Glare Sensitivity (imp:1.00) — The ability to see objects in the presence of a glare or bright lighting.
  Sound Localization (imp:1.00) — The ability to tell the direction from which a sound originated.

--- WORK ACTIVITIES ---
  Working with Computers (imp:4.96 lvl:5.83) — Using computers and computer systems (including hardware and software) to progra
  Analyzing Data or Information (imp:4.55 lvl:6.00) — Identifying the underlying principles, reasons, or facts of information by break
  Processing Information (imp:4.48 lvl:5.70) — Compiling, coding, categorizing, calculating, tabulating, auditing, or verifying
  Getting Information (imp:4.43 lvl:5.04) — Observing, receiving, and otherwise obtaining information from all relevant sour
  Updating and Using Relevant Knowledge (imp:4.22 lvl:5.52) — Keeping up-to-date technically and applying new knowledge to your job.
  Identifying Objects, Actions, and Events (imp:4.05 lvl:4.77) — Identifying information by categorizing, estimating, recognizing differences or 
  Thinking Creatively (imp:3.96 lvl:5.52) — Developing, designing, or creating new applications, ideas, relationships, syste
  Making Decisions and Solving Problems (imp:3.95 lvl:4.91) — Analyzing information and evaluating results to choose the best solution and sol
  Communicating with Supervisors, Peers, or Subordinates (imp:3.91 lvl:4.91) — Providing information to supervisors, co-workers, and subordinates by telephone,
  Interpreting the Meaning of Information for Others (imp:3.77 lvl:4.39) — Translating or explaining what information means and how it can be used.
  Organizing, Planning, and Prioritizing Work (imp:3.70 lvl:5.04) — Developing specific goals and plans to prioritize, organize, and accomplish your
  Establishing and Maintaining Interpersonal Relationships (imp:3.52 lvl:4.22) — Developing constructive and cooperative working relationships with others, and m
  Providing Consultation and Advice to Others (imp:3.43 lvl:4.61) — Providing guidance and expert advice to management or other groups on technical,
  Evaluating Information to Determine Compliance with Standards (imp:3.35 lvl:4.00) — Using relevant information and individual judgment to determine whether events o
  Developing Objectives and Strategies (imp:3.26 lvl:3.74) — Establishing long-range objectives and specifying the strategies and actions to 
  Developing and Building Teams (imp:3.13 lvl:3.39) — Encouraging and building mutual trust, respect, and cooperation among team membe
  Scheduling Work and Activities (imp:3.00 lvl:3.35) — Scheduling events, programs, and activities, as well as the work of others.
  Documenting/Recording Information (imp:3.00 lvl:3.52) — Entering, transcribing, recording, storing, or maintaining information in writte
  Training and Teaching Others (imp:2.96 lvl:3.74) — Identifying the educational needs of others, developing formal educational or tr
  Estimating the Quantifiable Characteristics of Products, Events, or Information (imp:2.91 lvl:3.09) — Estimating sizes, distances, and quantities; or determining time, costs, resourc
  Monitoring Processes, Materials, or Surroundings (imp:2.87 lvl:3.43) — Monitoring and reviewing information from materials, events, or the environment,
  Judging the Qualities of Objects, Services, or People (imp:2.83 lvl:3.13) — Assessing the value, importance, or quality of things or people.
  Coordinating the Work and Activities of Others (imp:2.82 lvl:3.61) — Getting members of a group to work together to accomplish tasks.
  Coaching and Developing Others (imp:2.67 lvl:3.78) — Identifying the developmental needs of others and coaching, mentoring, or otherw
  Communicating with People Outside the Organization (imp:2.61 lvl:3.04) — Communicating with people outside the organization, representing the organizatio
  Resolving Conflicts and Negotiating with Others (imp:2.57 lvl:3.30) — Handling complaints, settling disputes, and resolving grievances and conflicts, 
  Performing Administrative Activities (imp:2.52 lvl:3.04) — Performing day-to-day administrative tasks such as maintaining information files
  Guiding, Directing, and Motivating Subordinates (imp:2.43 lvl:2.96) — Providing guidance and direction to subordinates, including setting performance 
  Selling or Influencing Others (imp:2.30 lvl:2.13) — Convincing others to buy merchandise/goods or to otherwise change their minds or
  Monitoring and Controlling Resources (imp:2.22 lvl:2.87) — Monitoring and controlling resources and overseeing the spending of money.
  Staffing Organizational Units (imp:2.13 lvl:2.78) — Recruiting, interviewing, selecting, hiring, and promoting employees in an organ
  Assisting and Caring for Others (imp:1.82 lvl:1.45) — Providing personal assistance, medical attention, emotional support, or other pe
  Inspecting Equipment, Structures, or Materials (imp:1.59 lvl:1.26) — Inspecting equipment, structures, or materials to identify the cause of errors o
  Controlling Machines and Processes (imp:1.48 lvl:1.04) — Using either control mechanisms or direct physical activity to operate machines 
  Drafting, Laying Out, and Specifying Technical Devices, Parts, and Equipment (imp:1.48 lvl:1.00) — Providing documentation, detailed instructions, drawings, or specifications to t
  Repairing and Maintaining Electronic Equipment (imp:1.39 lvl:0.70) — Servicing, repairing, calibrating, regulating, fine-tuning, or testing machines,
  Performing for or Working Directly with the Public (imp:1.23 lvl:0.45) — Performing for people or dealing directly with the public. This includes serving
  Performing General Physical Activities (imp:1.09 lvl:0.26) — Performing general physical activities includes doing activities that require co
  Handling and Moving Objects (imp:1.09 lvl:0.22) — Using hands and arms in handling, installing, positioning, and moving materials,
  Operating Vehicles, Mechanized Devices, or Equipment (imp:1.09 lvl:0.17) — Running, maneuvering, navigating, or driving vehicles or mechanized equipment, s
  Repairing and Maintaining Mechanical Equipment (imp:1.00) — Servicing, repairing, adjusting, and testing machines, devices, moving parts, an

--- WORK STYLES ---
  Dependability (imp:5.00) — A tendency to be reliable, responsible, and consistent in meeting work-related o
  Attention to Detail (imp:4.00) — A tendency to be detail-oriented, organized, and thorough in completing work.
  Attention to Detail (imp:3.00) — A tendency to be detail-oriented, organized, and thorough in completing work.
  Integrity (imp:3.00) — A tendency to be honest and ethical at work.
  Dependability (imp:2.62) — A tendency to be reliable, responsible, and consistent in meeting work-related o
  Intellectual Curiosity (imp:2.16) — A tendency to seek out and acquire new work-related knowledge and obtain a deep 
  Cautiousness (imp:2.06) — A tendency to be careful, deliberate, and risk-avoidant when making work-related
  Integrity (imp:2.06) — A tendency to be honest and ethical at work.
  Cautiousness (imp:2.00) — A tendency to be careful, deliberate, and risk-avoidant when making work-related
  Achievement Orientation (imp:1.98) — A tendency to establish and maintain personally challenging work-related goals, 
  Innovation (imp:1.58) — A tendency to be inventive, to be imaginative, and to adopt new perspectives on 
  Perseverance (imp:1.55) — A tendency to exhibit determination and resolve to perform or complete tasks in 
  Tolerance for Ambiguity (imp:1.49) — A tendency to be comfortable with ambiguity and uncertainty at work.
  Initiative (imp:1.44) — A tendency to be proactive and take on extra responsibilities and tasks that may
  Adaptability (imp:1.29) — A tendency to be open to and comfortable with change, new experiences, or ideas 
  Self-Confidence (imp:1.05) — A tendency to believe in one's work-related capabilities and ability to control 
  Intellectual Curiosity (imp:1.00) — A tendency to seek out and acquire new work-related knowledge and obtain a deep 
  Stress Tolerance (imp:1.00) — A tendency to cope and function effectively in stressful situations at work.
  Self-Control (imp:0.66) — A tendency to remain calm and composed and to manage emotions effectively in res
  Cooperation (imp:0.64) — A tendency to be pleasant, helpful, and willing to assist others at work.
  Sincerity (imp:0.16) — A tendency to be genuine and sincere in interactions with others at work, withou
  Humility (imp:0.15) — A tendency to be modest and humble when interacting with others at work.
  Empathy (imp:0.04) — A tendency to show concern for others and be sensitive to others' needs and feel
  Social Orientation (imp:0.04) — A tendency to seek out, enjoy, and be energized by social interaction at work.
  Innovation () — A tendency to be inventive, to be imaginative, and to adopt new perspectives on 
  Achievement Orientation () — A tendency to establish and maintain personally challenging work-related goals, 
  Tolerance for Ambiguity () — A tendency to be comfortable with ambiguity and uncertainty at work.
  Initiative () — A tendency to be proactive and take on extra responsibilities and tasks that may
  Adaptability () — A tendency to be open to and comfortable with change, new experiences, or ideas 
  Self-Confidence () — A tendency to believe in one's work-related capabilities and ability to control 
  Perseverance () — A tendency to exhibit determination and resolve to perform or complete tasks in 
  Leadership Orientation () — A tendency to lead, take charge, offer opinions, and provide direction at work.
  Humility () — A tendency to be modest and humble when interacting with others at work.
  Sincerity () — A tendency to be genuine and sincere in interactions with others at work, withou
  Empathy () — A tendency to show concern for others and be sensitive to others' needs and feel
  Cooperation () — A tendency to be pleasant, helpful, and willing to assist others at work.
  Optimism () — A tendency to exhibit a positive attitude and positive emotions at work, even un
  Social Orientation () — A tendency to seek out, enjoy, and be energized by social interaction at work.
  Stress Tolerance () — A tendency to cope and function effectively in stressful situations at work.
  Self-Control () — A tendency to remain calm and composed and to manage emotions effectively in res
  Optimism (imp:-0.01) — A tendency to exhibit a positive attitude and positive emotions at work, even un
  Leadership Orientation (imp:-0.05) — A tendency to lead, take charge, offer opinions, and provide direction at work.

--- TRANSFERABLE SKILLS ---
  Programming (imp:3.75 lvl:3.75) — Writing computer programs for various purposes.
  Complex Problem Solving (imp:3.62 lvl:3.50) — Identifying complex problems and reviewing related information to develop and ev
  Systems Analysis (imp:3.50 lvl:3.50) — Determining how a system should work and how changes in conditions, operations, 
  Judgment and Decision Making (imp:3.38 lvl:3.62) — Considering the relative costs and benefits of potential actions to choose the m
  Systems Evaluation (imp:3.25 lvl:3.50) — Identifying measures or indicators of system performance and the actions needed 
  Coordination (imp:3.12 lvl:3.38) — Adjusting actions in relation to others' actions.
  Social Perceptiveness (imp:3.00 lvl:3.00) — Being aware of others' reactions and understanding why they react as they do.
  Time Management (imp:2.88 lvl:2.75) — Managing one's own time and the time of others.
  Persuasion (imp:2.75 lvl:3.12) — Persuading others to change their minds or behavior.
  Operations Analysis (imp:2.75 lvl:3.38) — Analyzing needs and product requirements to create a design.
  Negotiation (imp:2.62 lvl:2.62) — Bringing others together and trying to reconcile differences.
  Instructing (imp:2.62 lvl:3.38) — Teaching others how to do something.
  Service Orientation (imp:2.62 lvl:2.62) — Actively looking for ways to help people.
  Technology Design (imp:2.62) — Generating or adapting equipment and technology to serve user needs.
  Operations Monitoring (imp:2.50 lvl:2.25) — Watching gauges, dials, or other indicators to make sure a machine is working pr
  Quality Control Analysis (imp:2.38) — Conducting tests and inspections of products, services, or processes to evaluate
  Management of Personnel Resources (imp:2.12 lvl:2.00) — Motivating, developing, and directing people as they work, identifying the best 
  Operation and Control (imp:1.88) — Controlling operations of equipment or systems.
  Management of Material Resources (imp:1.88 lvl:1.62) — Obtaining and seeing to the appropriate use of equipment, facilities, and materi
  Management of Financial Resources (imp:1.75 lvl:1.38) — Determining how money will be spent to get the work done, and accounting for the
  Troubleshooting (imp:1.62 lvl:1.00) — Determining causes of operating errors and deciding what to do about it.
  Equipment Selection (imp:1.50) — Determining the kind of tools and equipment needed to do a job.
  Equipment Maintenance (imp:1.12 lvl:0.25) — Performing routine maintenance on equipment and determining when and what kind o
  Repairing (imp:1.12 lvl:0.25) — Repairing machines or systems using the needed tools.
  Installation (imp:1.00) — Installing equipment, machines, wiring, or programs to meet specifications.
BLS OEWS May 2025 — 67,140 employed nationally bls.gov/oes ↗ · Public Domain · US Government · retrieved 2026-06-02
--- NATIONAL WAGES ---
  total_employment : 67,140
  annual_median    : $139,500
  annual_pct10     : $86,240
  annual_pct25     : $109,370
  annual_pct75     : $169,290
  annual_pct90     : $204,000
  annual_mean      : $144,440
  hourly_median    : $67.07

--- GEOGRAPHIC DISPERSION ---
  highest_state    : California ($170,160)
  lowest_state     : Puerto Rico ($95,620)
  dispersion_ratio : 1.780x

--- TOP STATES BY WAGE (47 total) ---
  Professional, Scientific, and Technical Services emp:   24,320  median: $ 139,500
  Information                              emp:   10,540  median: $ 148,000
  Finance and Insurance                    emp:    9,370  median: $ 146,470
  Management of Companies and Enterprises  emp:    6,830  median: $ 139,320
  Administrative and Support and Waste Management and Remediation Services emp:    4,050  median: $ 149,490
  Health Care and Social Assistance        emp:    2,310  median: $ 129,310
  Wholesale Trade                          emp:    2,290  median: $ 134,340
  Manufacturing                            emp:    1,630  median: $ 134,520
  Educational Services                     emp:    1,610  median: $ 107,430
  Federal, State, and Local Government, excluding State and Local Government Schools and Hospitals and the U.S. Postal Service (OEWS Designation) emp:    1,230  median: $ 122,320

--- TOP INDUSTRIES BY EMPLOYMENT (18 total) ---
  Professional, Scientific, and Technical Services emp:   24,320  median: $ 139,500
  Information                              emp:   10,540  median: $ 148,000
  Finance and Insurance                    emp:    9,370  median: $ 146,470
  Management of Companies and Enterprises  emp:    6,830  median: $ 139,320
  Administrative and Support and Waste Management and Remediation Services emp:    4,050  median: $ 149,490
  Health Care and Social Assistance        emp:    2,310  median: $ 129,310
  Wholesale Trade                          emp:    2,290  median: $ 134,340
  Manufacturing                            emp:    1,630  median: $ 134,520
  Educational Services                     emp:    1,610  median: $ 107,430
  Federal, State, and Local Government, excluding State and Local Government Schools and Hospitals and the U.S. Postal Service (OEWS Designation) emp:    1,230  median: $ 122,320
Wikipedia — no exact match (0 words) N/A ↗ · CC BY-SA 4.0
exact_match_status : no_exact_match
matched_title      : N/A
match_score        : 0.0000
wikidata_qid       : N/A
word_count         : 0
wikipedia_url      : N/A
license            : CC BY-SA 4.0
fetched_at         : 2026-06-02T20:21:50.287525Z

--- SEMANTIC NEIGHBORS (5) ---

  Title: Information technology management (similarity: 0.2295)
  URL: https://en.wikipedia.org/wiki/Information_technology_management
  QID: Q1473265
  Extract: Information technology management is the discipline whereby all of the information technology resources of a firm are managed in accordance with its needs and priorities. Managing the responsibility within a company entails many of the basic management functions, like budgeting, staffing, change man

  Title: Data model (similarity: 0.3684)
  URL: https://en.wikipedia.org/wiki/Data_model
  QID: Q1172480
  Extract: A data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, re

  Title: Data and information visualization (similarity: 0.4516)
  URL: https://en.wikipedia.org/wiki/Data_and_information_visualization
  QID: Q133505171
  Extract: Data and information visualization is the practice of designing and creating graphic or visual representations of quantitative and qualitative data and information with the help of static, dynamic or interactive visual items. These visualizations are intended to help a target audience visually explo

  Title: Joe Caserta (similarity: 0.1538)
  URL: https://en.wikipedia.org/wiki/Joe_Caserta
  QID: Q109519757
  Extract: Joe Caserta is an American information specialist and author. He is best known as the founder and president of data and analytics consulting, architecture, and implementation firm Caserta founded in 2001. Management consulting firm McKinsey & Company acquired Caserta on June 1, 2022.

  Title: Big data (similarity: 0.2222)
  URL: https://en.wikipedia.org/wiki/Big_data
  QID: Q858810
  Extract: Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing software. Data with many entries (rows) offers greater statistical power, while data with higher complexity may lead to a higher false discovery rate.
Claude Inference — claude-sonnet-4-20250514 · confidence:high · $0.0478 inferred_at: 2026-06-03T13:55:18 UTC · Boise Standard inference pipeline v1.0
model_pass1          : claude-sonnet-4-20250514
model_pass2          : claude-haiku-4-5-20251001
inference_confidence : high
confidence_notes     : Strong confidence based on detailed O*NET data, comprehensive task descriptions, clear wage data from BLS OEWS May 2025, and well-defined skill requirements that distinguish this role from adjacent database and analytics positions.
inferred_at          : 2026-06-03T13:55:18.872158+00:00
tokens_input         : 4,435
tokens_output        : 4,290
cost_usd             : $0.047783
wikipedia_used       : False
wikipedia_title      : None
wikipedia_note       : No exact Wikipedia match found for Data Warehousing Specialists. The closest semantic neighbor 'Data and information visualization' relates to the broader data management field but focuses on presentation rather than the storage and integration aspects central to this role.

--- PROSE FIELDS ---

ROLE SUMMARY:
Data Warehousing Specialists design, implement, and maintain corporate data storage systems that consolidate information from multiple sources for analysis and reporting. They program and configure database warehouses, develop ETL (extract, transform, load) processes, and provide technical support to end users accessing warehouse data. These professionals bridge business requirements with technical implementation, ensuring data quality, structure, and accessibility for organizational decision-making.

DAY IN THE LIFE:
A Data Warehousing Specialist begins their day by monitoring overnight ETL processes and verifying data quality in warehouse systems. They spend time mapping data flows between source systems and data marts, often troubleshooting integration issues or modifying existing programs to meet new business requirements. Mid-day involves collaborating with stakeholders to understand data needs and designing warehouse database structures that optimize both data access and system performance. They analyze data patterns, develop process models for data sourcing and transformation, and implement comprehensive standards for warehouse organization. The day concludes with documenting procedures, coordinating with IT support teams, and planning system optimizations.

WHO THRIVES:
Professionals who excel as Data Warehousing Specialists possess strong analytical minds with exceptional attention to detail, as evidenced by the critical importance of dependability and detail orientation in their work styles. They demonstrate high levels of deductive and inductive reasoning abilities, allowing them to identify patterns in complex data relationships and solve intricate technical problems. The conventional-investigative RIASEC profile indicates they thrive on systematic work with clear procedures while enjoying intellectual challenges that require deep analysis. These individuals are comfortable working independently with computers and databases, possess strong written and oral communication skills for stakeholder interaction, and maintain the persistence needed for troubleshooting complex data integration issues.

CAREER ENTRY:
Entry into Data Warehousing requires a bachelor's degree, which 78.3% of professionals hold, typically in computer science, information systems, or related technical fields. New professionals often start with foundational experience in database administration, programming, or systems analysis before specializing in data warehousing concepts. The Job Zone 4 classification indicates considerable preparation is needed, including understanding of programming languages, database design principles, and ETL methodologies. Many professionals gain relevant experience through internships or entry-level positions in database administration or business intelligence roles.

CAREER TRAJECTORY:
Data Warehousing Specialists typically advance to senior technical roles such as Data Warehouse Architects, Database Architects, or Analytics Managers, leveraging their deep understanding of enterprise data systems. The strong overlap with Data Scientists and Business Intelligence Analysts creates pathways into strategic roles focused on advanced analytics and business insights. Many professionals progress into management positions overseeing data teams or move into specialized consulting roles helping organizations implement data warehousing solutions. The foundational skills in systems analysis and database design also enable transitions into broader software development or systems engineering roles.

MARKET INTELLIGENCE:
Data Warehousing Specialists command strong compensation with a median annual salary of $139,500 according to BLS OEWS May 2025, with the top 10% earning over $204,000. The field employs 67,140 professionals nationwide, concentrated in Professional, Scientific, and Technical Services (24,320 employed), Information (10,540), and Finance and Insurance (9,370) sectors. Geographic pay varies significantly, with California leading at $170,160 median salary compared to Puerto Rico at $95,620, representing a 1.78x ratio. The emphasis on hot technologies like Amazon AWS, Apache Hadoop, and cloud-based data solutions indicates growing demand driven by digital transformation and big data initiatives. Job Zone 4 classification suggests stable demand for skilled professionals as organizations increasingly rely on data-driven decision making.

AUTOMATION OUTLOOK:
Data Warehousing Specialists face moderate automation risk in routine ETL processes and data mapping activities, but their core work remains largely protected due to high cognitive demands. The emphasis on analyzing data, creative thinking (importance 4.0, level 5.5), and complex problem-solving indicates that strategic design and troubleshooting aspects of the role require human judgment. While automated tools may streamline data extraction and transformation processes, the need for systems analysis, stakeholder communication, and custom programming solutions ensures continued demand for human expertise in this field.

--- REASONED EDGES ---
  [skill_overlap] Database Architects (15-1243.00) — confidence:high
    reasoning: Both roles require high-level database design skills and share core competencies in systems analysis and data management.
    data: Programming skill importance 3.8
    data: Systems Analysis importance 3.5
    data: Database design knowledge
  [task_similarity] Database Administrators (15-1242.00) — confidence:high
    reasoning: Both roles involve database structure implementation, troubleshooting support, and data quality verification activities.
    data: Troubleshooting support tasks
    data: Database structure design
    data: Working with Computers importance 5.0
  [knowledge_overlap] Business Intelligence Analysts (15-2051.01) — confidence:high
    reasoning: Both require strong analytical skills for data analysis and share knowledge requirements in mathematics and business processes.
    data: Analyzing Data importance 4.5
    data: Mathematics knowledge importance 3.2
    data: Administration and Management knowledge 2.6
  [transferable_skill] Software Developers (15-1252.00) — confidence:medium
    reasoning: Programming and complex problem-solving skills transfer directly between roles, with similar systematic development approaches.
    data: Programming transferable skill 3.8
    data: Complex Problem Solving 3.6
    data: Written programming tasks
  [riasec_cluster] Data Scientists (15-2051.00) — confidence:medium
    reasoning: Both show conventional-investigative profiles with emphasis on systematic data work and analytical problem-solving.
    data: Conventional RIASEC score 6.38
    data: Investigative score 4.79
    data: Data analysis focus
  [job_zone] Computer Systems Analysts (15-1211.00) — confidence:high
    reasoning: Both require Job Zone 4 preparation with similar educational requirements and systems analysis competencies.
    data: Job Zone 4 classification
    data: Systems Analysis skill importance 3.5
    data: Bachelor's degree 78.3%

--- NORMALIZER SIGNALS ---
  match_keywords   : ['data warehouse', 'data warehousing', 'ETL', 'data integration', 'data modeling', 'warehouse database', 'data extraction', 'warehouse developer']
  exclude_keywords : ['data entry', 'data analyst', 'business analyst', 'database administrator', 'software developer']
  title_patterns   : ['Data Warehouse*', '*Warehouse*', 'ETL*', '*Data Warehouse*', 'Warehouse Developer']
  common_variations: ['Data Warehouse Developer', 'Data Warehouse Engineer', 'Data Warehouse Analyst', 'ETL Developer', 'Data Integration Specialist', 'Warehouse Database Developer', 'Data Warehouse Architect', 'Big Data Engineer']
Semantic Manifold — 40 terms · 5 provenance layers employment_word_extractor.py · sources: onet_tasks | onet_dimensions | dwas | wikipedia | inference · Constitutional Law III
total_terms    : 40
top_words      : ['tendency', 'others', 'equipment', 'procedures', 'principles', 'design', 'management', 'software', 'includes', 'control', 'objects', 'warehouse', 'quality', 'standards', 'analysis', 'techniques', 'warehousing', 'problems', 'performance', 'ideas']
source_layers  : onet_tasks | onet_dimensions | dwas | wikipedia | inference

TERM                    COUNT     FREQ  DOMINANT SOURCE      SOURCE BREAKDOWN
──────────────────────────────────────────────────────────────────────────────────────────
tendency                   42  0.01515  onet_dimensions      onet_dimensions:100%
others                     38  0.01371  onet_dimensions      onet_dimensions:100%
equipment                  23  0.00830  onet_dimensions      onet_dimensions:100%
procedures                 20  0.00722  onet_dimensions      onet_dimensions:40%  dwas:30%  onet_tasks:20%
principles                 17  0.00613  onet_dimensions      onet_dimensions:94%  inference:6%
design                     16  0.00577  onet_dimensions      onet_dimensions:38%  inference:25%  onet_tasks:19%
management                 16  0.00577  onet_dimensions      onet_dimensions:44%  wikipedia:25%  dwas:19%
software                   12  0.00433  dwas                 dwas:33%  onet_dimensions:25%  onet_tasks:17%
includes                   12  0.00433  onet_dimensions      onet_dimensions:100%
control                    12  0.00433  onet_dimensions      onet_dimensions:100%
objects                    12  0.00433  onet_dimensions      onet_dimensions:100%
warehouse                  11  0.00397  onet_tasks           onet_tasks:55%  inference:45%
quality                    11  0.00397  onet_dimensions      onet_dimensions:55%  onet_tasks:18%  inference:18%
standards                  11  0.00397  onet_dimensions      onet_dimensions:73%  onet_tasks:9%  dwas:9%
analysis                   11  0.00397  inference            inference:45%  onet_dimensions:36%  onet_tasks:18%
techniques                 11  0.00397  onet_dimensions      onet_dimensions:91%  onet_tasks:9%
warehousing                11  0.00397  inference            inference:91%  onet_tasks:9%
problems                   11  0.00397  onet_dimensions      onet_dimensions:82%  dwas:9%  inference:9%
performance                11  0.00397  onet_dimensions      onet_dimensions:64%  dwas:27%  inference:9%
ideas                      11  0.00397  onet_dimensions      onet_dimensions:100%
technical                  10  0.00361  inference            inference:60%  onet_dimensions:30%  onet_tasks:10%
needs                      10  0.00361  onet_dimensions      onet_dimensions:80%  wikipedia:10%  inference:10%
resources                  10  0.00361  onet_dimensions      onet_dimensions:90%  wikipedia:10%
materials                  10  0.00361  onet_dimensions      onet_dimensions:100%
quickly                    10  0.00361  onet_dimensions      onet_dimensions:90%  wikipedia:10%
body                       10  0.00361  onet_dimensions      onet_dimensions:100%
activities                 10  0.00361  onet_dimensions      onet_dimensions:90%  inference:10%
orientation                10  0.00361  onet_dimensions      onet_dimensions:90%  inference:10%
programming                 9  0.00325  inference            inference:33%  onet_tasks:22%  onet_dimensions:22%
business                    9  0.00325  inference            inference:56%  onet_tasks:22%  onet_dimensions:11%
rules                       9  0.00325  onet_dimensions      onet_dimensions:89%  onet_tasks:11%
understand                  9  0.00325  onet_dimensions      onet_dimensions:78%  wikipedia:11%  inference:11%
monitoring                  9  0.00325  onet_dimensions      onet_dimensions:89%  inference:11%
technology                  9  0.00325  onet_dimensions      onet_dimensions:44%  wikipedia:33%  dwas:22%
human                       9  0.00325  onet_dimensions      onet_dimensions:78%  inference:22%
needed                      9  0.00325  onet_dimensions      onet_dimensions:78%  inference:22%
database                    8  0.00289  inference            inference:88%  onet_tasks:12%
structures                  8  0.00289  onet_dimensions      onet_dimensions:62%  onet_tasks:12%  wikipedia:12%
programs                    8  0.00289  onet_dimensions      onet_dimensions:50%  onet_tasks:25%  dwas:12%
computer                    8  0.00289  onet_dimensions      onet_dimensions:38%  dwas:38%  onet_tasks:12%
◈ Boise Standard Employment Graph · 15-1243.01 · built 2026-06-02 · Sources declared above are authoritative originals. This page synthesizes but does not replace them. Every claim traceable. Full provenance. Constitutional Law I.
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