Top Data & Analytics Jobs in Washington, DC

Designs and implements data architecture solutions, including data models, data flows, dictionaries, warehouses, and data lakes. Integrates data from multiple sources, ensures quality, integrity, and security, troubleshoots architecture and ETL issues, reviews technical configurations, and guides development teams. Collaborates with stakeholders, stays current on data management practices, and mentors junior staff supporting government programs.

Develop and maintain software, data pipelines, ETL workflows, automation, and databases supporting SAPRO's mission. Use R, SQL, Python, and Databricks for data extraction, transformation, manipulation, and analytical workflows. Troubleshoot and optimize pipelines, enhance software, define technical requirements, and collaborate with technical and non-technical stakeholders. The role requires at least three years of data engineering experience and an active Secret clearance.

Analyze, clean, validate, and transform data from multiple sources; build Kibana dashboards and visualizations; maintain data pipelines and self-service analytics assets; document data models and workflows; and translate findings into actionable recommendations for technical and non-technical stakeholders.

Designs, builds, and maintains scalable Azure data pipelines and ELT frameworks using Databricks, SQL, Python, and PySpark. Implements Azure DevOps CI/CD, monitoring, security, infrastructure automation, and production support. Collaborates with BI teams on Power BI datasets, documents data solutions, participates in Agile delivery, and mentors junior engineers. The role requires strong data modeling, structured and semi-structured data expertise, performance tuning, and data governance awareness.

Supports social listening and digital analytics by developing search queries, organizing online conversation data, identifying trends and themes, and translating findings into concise insights, narratives, presentations, and reports. The intern will also learn analytical tools, apply new methodologies, and support internal AI projects while managing deadlines and collaborating effectively.

Designs, builds, and operates enterprise data lakes, warehouses, lakehouses, ETL/ELT pipelines, databases, and reporting platforms. Prepares governed, model-ready data for AI and machine learning, supports feature stores and embedding workflows, administers relational databases, optimizes queries and dashboards, and ensures data quality, security, availability, and disaster recovery. Collaborates with technical and business teams, reports to senior management, and mentors data engineers.

Analyze and integrate client and acquisition data, develop analytical methodologies, maintain databases, create reports and technical deliverables, conduct research and reviews, troubleshoot data issues, and provide recommendations. The role also supports project objectives, strategic direction, system testing and implementation, and client relationship management.

Lead migration of Informatica PowerCenter ETL workloads from on-premises Oracle infrastructure to Oracle Cloud Infrastructure. Assess, configure, migrate, validate, troubleshoot, and optimize enterprise ETL processes across environments. Develop data reconciliation and source-to-target validation, resolve performance and connectivity issues, coordinate cloud and database dependencies, and maintain migration documentation, test plans, runbooks, and recovery procedures. Support production readiness, change control, defect resolution, security processes, and knowledge transfer for the VA Enterprise Data Warehouse.

Supports quantitative and qualitative primary research engagements, including questionnaire and discussion guide development, survey specifications, fieldwork, data cleaning, tabulation, analysis, focus group logistics, and quality control. Prepares presentations, data tables, toplines, and findings summaries; coordinates with vendors and senior team members; tracks timelines and contributes to improving research processes and AI-enabled methodologies.

Develops dashboards, reports, scorecards, and analytical products using BI and visualization tools. Analyzes and integrates data from multiple sources, performs trend and performance analysis, translates stakeholder needs into reporting requirements, and presents insights to technical and non-technical audiences. The role also supports reporting validation, quality controls, data governance, documentation, and collaboration with data engineers, data scientists, and federal program stakeholders.