Top Senior Data & Analytics Jobs in Washington, DC

Analyze Medicaid and T-MSIS data to implement CMS payment model functions, including attribution, payment calculations, and quality measurement. Translate policy into specifications, SQL code, analytic files, and documented methodologies. Assess cross-state data quality, link Medicaid and Medicare sources, perform quality assurance, reconcile results, and communicate findings to technical and non-technical audiences. The role also involves code review, knowledge sharing, and supporting federal healthcare consulting engagements.

Lead data analysis projects to help merchant partners understand Upside's impact, manage analytics relationships, and improve product strategy.

Designs, executes, and analyzes AI-powered qualitative and quantitative opinion research. The role manages survey methodology, sampling, fieldwork, analysis, synthesis, reporting, client presentations, project budgets, and timelines. It also pilots AI applications, collaborates on intelligence platforms, translates data into strategic narratives, mentors junior staff, and supports proposals and business development.

Administer and optimize enterprise Microsoft SQL Server environments, including installation, configuration, performance tuning, security, backups, recovery, maintenance, upgrades, and high availability. Diagnose complex production issues, support migrations and deployments, collaborate with developers and infrastructure teams, monitor capacity and performance, and maintain technical documentation and operational procedures.

Leads the Enterprise Control Tower technical team and develops the enterprise data foundation supporting AI applications. Responsibilities include creating data products and ontologies, managing technical requirements and governance, overseeing engineering operations, mitigating technical risks, managing budgets and staffing, building stakeholder relationships, and hiring and developing architects and engineers. The role requires strategic leadership, enterprise data platform ownership, and delivery of measurable business value.

Analyzes, interprets, organizes, and visualizes large datasets for agency personnel and stakeholders. Responsibilities include collecting data, producing reports, charts, and Power BI dashboards, managing data compilation and archiving, entering data into databases and spreadsheets, and supporting ad hoc analysis projects. The role requires an active Top Secret clearance, a bachelor's degree, at least five years of data analysis experience, and proficiency with Excel, Power BI, or similar tools.

Design, build, and maintain data pipelines, analytics-ready datasets, reports and dashboards on cloud platforms (Databricks, Snowflake, Azure). Partner with stakeholders to translate requirements, perform analysis and modeling, troubleshoot data issues, apply development best practices, and share knowledge across teams.

Administers and supports business software and trip management systems, manages user accounts and telecommunications systems, resolves technical issues, trains users, and maintains hardware and software inventories. Develops SQL-based reports using Crystal Reports and SSRS, analyzes transportation utilization data, and produces contractual and ad hoc reporting. Provides 24/7 support, assists with requirements and process analysis, and travels to satellite offices as needed.

Maintain investment data integrity through validation controls, data quality improvements, transaction implementations, analytics tool support, and process automation. Investigate data issues, identify root causes, recommend resolutions, and support migration to an investment data warehouse. Collaborate with investment teams, IT, Accounting, and other corporate partners while maintaining procedures and supporting concurrent projects. The role requires fixed-income investment knowledge and experience with Bloomberg, BlackRock Aladdin, Excel, Power BI, SQL, Snowflake, and Python.

Leads Oracle Fusion Cloud data migration and ETL initiatives, including source analysis, data mapping, extraction, cleansing, transformation, validation, loading, reconciliation, mock migrations, cutover, and legacy decommissioning. Develops ETL workflows and automation using Oracle and third-party tools, troubleshoots data loads, ensures data quality and governance, and collaborates with consultants, architects, business users, and stakeholders through testing and deployment.