Occupation · SOC 15-1243.01
Data Warehousing Specialists
Design, model, or implement corporate data warehousing activities. Program and configure warehouses of database information and provide support to warehouse users.
Median wage
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Projected growth
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Annual openings
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per year
Employed (US)
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Job Zone 4
Typical preparation
Considerable preparation
Stackable credential programs
3,943 mapped
Core skills
Reading ComprehensionCritical ThinkingProgrammingComplex Problem SolvingSystems AnalysisActive ListeningSpeakingJudgment and Decision MakingWritingSystems EvaluationCoordinationSocial PerceptivenessMathematicsActive LearningTime ManagementMonitoringPersuasionOperations AnalysisTechnology DesignService OrientationNegotiationLearning StrategiesInstructingOperations MonitoringQuality Control AnalysisManagement of Personnel ResourcesScienceOperation and ControlManagement of Material ResourcesManagement of Financial ResourcesTroubleshootingEquipment SelectionRepairingEquipment MaintenanceInstallation
Knowledge areas
Computers and ElectronicsMathematicsEnglish LanguageDesignEngineering and TechnologyAdministration and ManagementCustomer and Personal ServiceEducation and TrainingEconomics and AccountingProduction and ProcessingTelecommunicationsPersonnel and Human ResourcesAdministrativeSales and MarketingLaw and GovernmentCommunications and MediaPsychologyGeographySociology and AnthropologyPhysicsTransportationPublic Safety and SecurityMedicine and DentistryForeign LanguagePhilosophy and TheologyFine ArtsBuilding and ConstructionMechanicalHistory and ArcheologyTherapy and CounselingFood ProductionChemistryBiology
Technology & tools
Adaptive Metadata ManagerAdeptia ETL SuiteAdvanced business application programming ABAPAltova MapForceAmazon DynamoDBAmazon Elastic Compute Cloud EC2Amazon RedshiftAmazon Simple Storage Service S3Amazon Web Services AWS softwareApache AvroApache CassandraApache FlumeApache HBaseApache HTTP ServerApache HadoopApache HiveApache KafkaApache OozieApache PigApache SolrApache SparkApache SqoopApache Subversion SVNApatarApple macOSAster Data nClusterAtlassian JIRABashBlackbaud The Raiser's EdgeCC#C++Cloudera ImpalaCloverETLCodeFutures dbShardsCoglin Mill RODINCommon business oriented language COBOLCustomer information control system CICSESRI ArcGIS softwareEclipse IDE
Representative tasks
Working with ComputersAnalyzing Data or InformationProcessing InformationGetting InformationUpdating and Using Relevant KnowledgeIdentifying Objects, Actions, and EventsThinking CreativelyMaking Decisions and Solving ProblemsCommunicating with Supervisors, Peers, or SubordinatesInterpreting the Meaning of Information for OthersOrganizing, Planning, and Prioritizing WorkEstablishing and Maintaining Interpersonal RelationshipsProviding Consultation and Advice to OthersEvaluating Information to Determine Compliance with StandardsDeveloping Objectives and StrategiesDeveloping and Building TeamsScheduling Work and ActivitiesDocumenting/Recording InformationTraining and Teaching OthersEstimating the Quantifiable Characteristics of Products, Events, or InformationMonitoring Processes, Materials, or SurroundingsJudging the Qualities of Objects, Services, or PeopleCoordinating the Work and Activities of OthersCoaching and Developing OthersCommunicating with People Outside the OrganizationResolving Conflicts and Negotiating with OthersPerforming Administrative ActivitiesGuiding, Directing, and Motivating SubordinatesSelling or Influencing OthersMonitoring and Controlling ResourcesStaffing Organizational UnitsAssisting and Caring for OthersInspecting Equipment, Structures, or MaterialsDrafting, Laying Out, and Specifying Technical Devices, Parts, and EquipmentControlling Machines and ProcessesRepairing and Maintaining Electronic EquipmentPerforming for or Working Directly with the PublicPerforming General Physical ActivitiesOperating Vehicles, Mechanized Devices, or EquipmentHandling and Moving Objects
Competency framework
Skill expectations by proficiency level.
emerging
Data warehouse process models — identify and document sourcing, loading, transformation, and extraction steps under direct supervision in a structured enterprise environment.Warehouse data quality — perform basic verification checks on structure and accuracy using predefined validation scripts in a team-supported data environment.Data mapping documentation — assist in mapping data fields between source systems and data warehouses following established templates and guidelines.Data extraction procedures — execute existing ETL scripts from administration or billing systems under senior specialist direction in a production support setting.Warehouse database structures — assist in designing simple schemas by applying foundational relational database principles in a supervised project environment.Data warehouse standards — review and apply existing organizational naming conventions and structural standards when working with warehouse elements.Troubleshooting support — document and escalate data warehouse incidents by following established triage protocols in a helpdesk-supported environment.Programming tasks — modify small, well-defined segments of existing ETL or reporting code using current languages under code-review oversight.Metadata management software — navigate and query metadata repositories to locate data lineage information under guided instruction in a warehouse environment.Technical documentation — read and interpret system specifications, data dictionaries, and warehouse design documents to support assigned task completion.
developing
Data warehouse process models — design and refine ETL process flows covering sourcing, transformation, and loading with reduced oversight in an enterprise data environment.Warehouse data quality — conduct systematic accuracy and structural audits using query tools and profiling software, resolving common anomalies independently.Data mapping specifications — produce and validate end-to-end field mapping documents between source systems, data warehouses, and data marts for routine integration projects.Data extraction procedures — develop and implement extraction routines from billing, claims, or administrative systems using current ETL platforms in a multi-source environment.Warehouse database structures — design and deploy normalized and dimensional database schemas to meet defined business requirements in a managed data warehouse setting.Warehouse standards maintenance — update and enforce data architecture naming conventions, model standards, and tooling guidelines across assigned warehouse components.Troubleshooting coordination — diagnose and resolve moderate data warehouse failures by analyzing logs, tracing data flows, and coordinating fixes with application teams.Program development — write and test new ETL programs or reporting scripts using object-oriented or procedural languages to satisfy defined customer requirements.Systems analysis — evaluate source system data structures and integration points to identify compatibility issues before warehouse load cycles begin.Stakeholder communication — explain data warehouse processes and integration decisions clearly to business analysts and project managers in cross-functional meetings.
proficient
Data warehouse process models — architect comprehensive end-to-end process models spanning sourcing, transformation, loading, and extraction layers across complex, multi-domain enterprise environments.Data quality assurance — design and execute advanced validation frameworks that detect structural defects, referential integrity failures, and semantic inconsistencies across the full warehouse scope.Cross-system data mapping — lead the creation of authoritative mapping specifications integrating heterogeneous source systems, enterprise data warehouses, and subject-area data marts.Extraction procedure engineering — engineer robust, high-performance data extraction solutions from diverse operational systems, incorporating error handling and incremental load strategies.Warehouse database architecture — design scalable star and snowflake schemas, partitioning strategies, and indexing plans optimized for analytical query performance in large-scale environments.Standards governance — develop and enforce enterprise-wide data warehouse design standards covering architectures, models, tooling selection, and database nomenclature.Troubleshooting leadership — independently diagnose and resolve complex, non-routine data warehouse incidents including performance degradation, data corruption, and pipeline failures.Advanced programming — write, optimize, and refactor complex ETL programs and stored procedures using current languages and technologies to meet evolving customer and system requirements.Systems evaluation — assess warehouse platform performance, scalability, and fitness-for-purpose against business objectives, recommending architectural improvements based on evidence.Critical problem solving — apply deductive and inductive reasoning to resolve ambiguous data integration challenges that span multiple business domains and technology stacks.
advanced
Enterprise data warehouse strategy — define and drive the long-term vision, roadmap, and investment priorities for data warehousing capabilities across the organization.Process model governance — establish organizational standards for warehouse process model design, ensuring consistency, reusability, and alignment with enterprise data strategy.Data quality policy — develop and institutionalize data quality policies, metrics, and accountability structures that govern warehouse accuracy and trustworthiness at organizational scale.Architectural leadership — lead the design of next-generation warehouse and data platform architectures, incorporating cloud, lakehouse, or hybrid patterns to meet strategic business needs.Standards body leadership — chair or lead enterprise data governance committees that define, publish, and evolve data warehouse standards, taxonomies, and architectural principles.Organizational troubleshooting capability — build and mature a warehouse support function, including runbooks, escalation frameworks, and on-call structures that ensure platform reliability.Technology evaluation and adoption — evaluate emerging warehouse platforms, ETL tools, and metadata management solutions, making adoption recommendations with measurable business impact.Talent development — mentor and coach data warehousing specialists across all experience levels, designing learning pathways that elevate team capability and bench strength.Cross-functional alignment — partner with executive stakeholders, data governance officers, and enterprise architects to translate business strategy into actionable data warehousing initiatives.Innovation and research — lead proof-of-concept initiatives exploring advanced data integration, real-time warehouse patterns, or AI-augmented ETL processes to sustain competitive organizational advantage.
Also known as
27 alternate job titles map to this occupation.
Analytics ManagerBig Data EngineerData Integrity SpecialistData Management EngineerData Management ManagerData Management SpecialistData Migration SpecialistData Quality AnalystData SpecialistData Storage SpecialistData Warehouse AnalystData Warehouse DeveloperData Warehouse EngineerData Warehouse ETL Developer (Data Warehouse Extract, Transform, and Load Developer)Data Warehouse ProgrammerData Warehouse Solution ArchitectData Warehouse SpecialistData Warehousing EngineerData Warehousing SpecialistDatabase SpecialistETL Developer (Extract-Transform-Load Developer)ETL Tester (Extract-Transform-Load Tester)IT Data Specialist (Information Technology Data Specialist)Product Data SpecialistProvider Data SpecialistResearch Data SpecialistStorage Engineer