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Data Warehouse Engineer Jobs in Virginia (NOW HIRING)

Data Engineer

Mclean, VA · On-site

$115K - $139K/yr

Data Engineer Location: Mclean, VA Duration: Long term contract Note: Looking for Ex-Capital One ... Experience with Snowflake or other cloud-based data warehouses. * Knowledge of data modeling, data ...

Data Engineer

Reston, VA · On-site

$119K - $143K/yr

Required : • Bachelor's Degree. • Computer Science, Information Technology or Engineering or related field. • Total of 10 Years of IT Experience predominantly in Data Integration/Data Warehouse ...

Lead Data Engineer (Hybrid)

Reston, VA · On-site

$121K - $145K/yr

The Lead Data Engineer is responsible for orchestrating, deploying, maintaining and scaling Cloud ... Develops and maintains infrastructure systems (e.g., data warehouses, data lakes) including data ...

Design, build, and maintain our enterprise data warehouse on Snowflake, ensuring optimal ... Qualifications * 6+ years of hands-on experience in data engineering, data warehousing, or ...

Staff Data Engineer

Arlington, VA · On-site +1

$145K - $175K/yr

Design, build, and maintain our enterprise data warehouse on Snowflake, ensuring optimal ... Qualifications * 6+ years of hands-on experience in data engineering, data warehousing, or ...

Fracsys Inc is hiring a AWS Data Engineer position. The ideal candidate must have at least 8+ years ... He or she must be responsible for successful technical delivery of Data Warehousing and Business ...

Fracsys Inc is hiring a AWS Data Engineer position. The ideal candidate must have at least 8+ years ... He or she must be responsible for successful technical delivery of Data Warehousing and Business ...

Ashburn, VA (onsite) Contract * 8+ years as a Data Warehouse Engineer or DBA. * 3+ years of hands on BigQuery administration in production. * Strong SQL performance tuning and query optimization ...

Requirement/Must Have: * 5+ years of experience in data profiling. * 5+ years of experience in data modeling. * 5+ years of experience in SQL Server data mart development. * 5+ years of experience in ...

... Programmer or Database Administrator developing database applications using complex SQL queries. · Experience with SSIS as the ETL tool for Data Warehouse development. · Experience with Azure ...

Fracsys Inc is hiring a AWS Data Engineer position. The ideal candidate must have at least 8+ years ... He or she must be responsible for successful technical delivery of Data Warehousing and Business ...

Data Science and Data Engineering Job Qualifications: Skills: Data Warehouse Architecture, Data Warehouse Management, Microsoft SQL Server Administration Certifications: None Experience: 15 + years ...

Data Engineer

Quantico, VA

$123K - $148K/yr

Build and maintain data warehouse environments and support data modeling efforts * Ensure data ... Promote best practices in data engineering, governance, and data lifecycle management * Support ...

Sr. Data Engineer

Richmond, VA · Remote

$104K - $142K/yr

Our Data Engineering team builds and maintains the operational data foundation that powers real ... Translate client loyalty program requirements into production-ready data warehouse structures ...

Showing results 21-40

Data Warehouse Engineer information

See Virginia salary details

$85.8K

$125.4K

$159.1K

How much do data warehouse engineer jobs pay per year?

As of Aug 17, 2026, the average yearly pay for data warehouse engineer in Virginia is $125,414.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,500.00 and $135,300.00 per year, depending on experience, location, and employer.

What is a data warehouse engineer?

Data Warehouse Engineers are IT professionals who design, build, and maintain systems used for storing and analyzing large volumes of data. They create data models, implement ETL (Extract, Transform, Load) processes, and ensure data integrity and optimized performance within the data warehouse environment. Their work enables organizations to efficiently store data from various sources and make it accessible for business intelligence and analytics. Data Warehouse Engineers often collaborate with data analysts, data scientists, and database administrators to support informed decision-making.

What are the key skills and qualifications needed to thrive as a data warehouse engineer?

To thrive as a Data Warehouse Engineer, you need expertise in database design, ETL processes, SQL, and data modeling, typically supported by a degree in computer science or a related field. Familiarity with tools like Microsoft SQL Server, Oracle, Informatica, and cloud platforms such as AWS Redshift or Google BigQuery, as well as certifications in these technologies, are valuable. Strong problem-solving abilities, attention to detail, and effective communication help you collaborate with stakeholders and address data challenges efficiently. These skills ensure the reliable integration, storage, and retrieval of high-quality data, which is critical for business intelligence and decision-making.

What are some common challenges data warehouse engineers face when integrating data from multiple sources?

Data Warehouse Engineers often encounter challenges such as data inconsistency, varying data formats, and incomplete or duplicate records when integrating information from diverse systems. Addressing these issues requires careful planning, robust ETL (Extract, Transform, Load) processes, and close collaboration with source system owners and data analysts. Additionally, ensuring data quality and maintaining up-to-date documentation are crucial to support efficient troubleshooting and future scalability.

What is the difference between Data Warehouse Engineer vs Data Analyst?

AspectData Warehouse EngineerData Analyst
CredentialsBachelor's in CS, Data Science, or related; certifications like AWS, Google CloudBachelor's in Statistics, Math, or related; certifications like Microsoft Data Analyst
Work EnvironmentDesigning, building, maintaining data warehouses; working with ETL toolsAnalyzing data, creating reports, visualizations
Industry UsageUsed in organizations managing large-scale data infrastructureUsed across industries for business insights and decision-making

While both roles work with data, Data Warehouse Engineers focus on building and maintaining data storage systems, whereas Data Analysts interpret data to generate insights. They often collaborate but have distinct technical and functional responsibilities.

What does a data warehouse engineer do?

A data warehouse engineer designs, develops, and maintains data storage systems that aggregate and organize large volumes of data from various sources. They use tools like SQL, ETL processes, and data modeling to ensure data is accessible, accurate, and optimized for analysis. Their work supports business intelligence and decision-making processes.

What are popular job titles related to Data Warehouse Engineer jobs in Virginia?

For Data Warehouse Engineer jobs in Virginia, the most frequently searched job titles are:

Infographic showing various Data Warehouse Engineer job openings in Virginia as of August 2026, with employment types broken down into 54% Full Time, and 46% Contract. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $125,414 per year, or $60.3 per hour.

Data Warehouse Subject Matter Expert

Diaconia

Merrifield, VA • On-site

$150K - $220K/yr

Full-time

Posted 26 days ago


Job description

Job Type
Full-time
Description
Diaconia is seeking a Data Warehouse Subject Matter Expert to support the Client's Enterprise Data Modernization Program (Vortex). This is a proposal-critical Key Personnel role responsible for leading Enterprise Data Warehouse execution across a large, mission-critical SQL Server-based data environment supporting Client reporting, SearchPlus, APIs, AI/ML enrichment, and mission-user data access.
The successful candidate must be more than a traditional SQL Server DBA. This role requires a senior EDW leader who can guide data warehouse development, ETL sustainment, dimensional modeling, production support, performance tuning, data quality, release execution, modernization planning, and technical coordination across a complex federal data ecosystem.
Key Responsibilities
• Lead the EDW team responsible for development, sustainment, modernization, troubleshooting, and production support of Client's enterprise data warehouse environment.
• Provide hands-on technical leadership for SQL Server EDW design, dimensional modeling, ETL development, data ingestion, data validation, performance tuning, release support, and operational reliability.
• Maintain and enhance Kimball-style dimensional structures, including fact tables, dimension tables, star schemas, conformed dimensions, surrogate keys, slowly changing dimensions, and reporting-ready data models.
• Design, develop, review, troubleshoot, optimize, and maintain SSIS packages, T-SQL scripts, stored procedures, functions, triggers, indexes, jobs, views, and other EDW database objects.
• Support recurring production releases, including release planning, deployment coordination, regression testing, data validation, rollback planning, documentation, and post-release verification.
• Lead root-cause analysis for EDW defects, data quality issues, ETL failures, report discrepancies, performance degradation, job failures, and production incidents.
• Coordinate EDW work with downstream consumers, including Power BI, SSRS, enterprise reporting, SearchPlus/OpenSearch, APIs, AI/ML models, dashboards, and mission-user applications.
• Support modernization planning for EDW architecture, cloud readiness, metadata, lineage, ELT, data quality, data observability, automation, and API-enabled data access.
• Develop and maintain source-to-target mappings, ETL documentation, data dictionaries, data lineage artifacts, data validation procedures, operational runbooks, and technical design documentation.
• Support performance optimization across large SQL Server databases, including indexing, partitioning, query tuning, statistics maintenance, execution plan analysis, storage optimization, and workload monitoring.
Support high availability, disaster recovery, backup/recovery, failover testing, security patching, access controls, STIG/security compliance, and production database reliability
• Support Agile or Kanban delivery, including backlog refinement, sprint planning, daily standups, technical estimation, demonstrations, retrospectives, and status reporting.
Mentor data engineers, ETL developers, DBAs, reporting developers, and analysts on EDW standards, development patterns, data quality practices, and production support expectations
Requirements
Minimum Required Qualifications
• Active U.S. government Secret clearance or higher required at proposal submission.
• U.S. Citizenship required.
• SME labor-category compliant education and experience: Bachelor's degree with 10+ years of relevant experience; less than a Bachelor's degree requires 14+ years of relevant experience; Master's degree or higher may qualify with 8+ years of relevant experience.
• For this role, Diaconia is seeking 15+ years of total database, data warehouse, data engineering, or related data management experience due to the scale and complexity of the Client's Vortex environment.
• 12+ years of hands-on SQL Server experience.
• Experience supporting large SQL Server databases or enterprise data warehouse environments, preferably 5 TB or larger, billion-row scale, or hundreds of tables.
• Experience leading or serving as a senior technical SME for an enterprise data warehouse team, data engineering team, ETL team, or production database/data platform team.
• Hands-on experience with SQL Server EDW development, administration, performance tuning, data modeling, ETL, production support, and release execution.
• Experience with Kimball-style dimensional modeling, including fact/dimension design, star schemas, conformed dimensions, surrogate keys, slowly changing dimensions, and reporting-ready data marts.
• Experience with SSIS, SSRS, SSAS, Power BI, T-SQL, SQL Agent jobs, stored procedures, indexes, views, triggers, functions, and SQL Server performance tools.
• Experience developing, maintaining, or troubleshooting ETL pipelines and data transformation workflows across multiple source systems.
• Experience creating or maintaining source-to-target mappings, data dictionaries, ETL specifications, lineage documentation, data validation rules, and technical design documentation.
• Experience working in Agile, Scrum, or Kanban environments with recurring releases and production support responsibilities.
• Experience supporting security, access controls, auditing, data integrity, backup/recovery, HA/DR, and compliance in a federal or similarly regulated production environment.
Strong written and verbal communication skills, with the ability to explain technical risks, tradeoffs, data quality issues, and modernization recommendations to technical and non-technical stakeholders
Preferred Qualifications
• Current or prior federal, law enforcement, public safety, homeland security, intelligence, financial-crimes, investigative, or sensitive federal mission experience.
• Experience with EDW environments comparable to client Vortex scale: 25+ source systems, 200+ ETL workflows, hundreds of tables, tens of terabytes of data, and recurring monthly or more frequent releases.
• Experience with Python, R, PowerShell, or automation scripting for data validation, ETL support, operational monitoring, testing, or data quality analysis.
• Experience with cloud data modernization using AWS, Azure, Azure Government, SQL Server on cloud infrastructure, cloud storage, data lake, lakehouse, Snowflake, Databricks, Azure Data Factory, AWS Glue, or similar tools.
• Experience with metadata management, data lineage, data quality tooling, data cataloging, data observability, data governance, or master/reference data management.
• Experience integrating EDW outputs with Power BI, SSRS, Power BI Report Server, enterprise reporting portals, APIs, SearchPlus/OpenSearch, ElasticSearch/OpenSearch indexes, or AI/ML enrichment pipelines.
• Experience supporting FedRAMP, FISMA, NIST, STIG, CUI, Privacy Act, law enforcement sensitive, or similarly controlled data environments.
• Experience with CI/CD, DevSecOps, automated testing, database deployment automation, version control, code review, and release management for database/ETL assets.
• Microsoft SQL Server, Azure Database Administrator, Azure Data Engineer, AWS, Snowflake, Databricks, DAMA, or related certifications.
Salary Description
$150,000 - $220,000