Top Senior Data & Analytics Jobs in Washington, DC

Provides analytics-driven strategic advice for mergers, acquisitions, and other transactions. Responsibilities include analyzing contract data, developing algorithms and predictive models, integrating data sources, building pipelines, creating dashboards, validating data integrity and security, and identifying risks and compliance indicators. The role also involves client collaboration, mentoring junior staff, and delivering data-driven insights using Python and machine learning.

Lead design and implementation of data infrastructure, pipelines, and warehouses using Azure Data Factory, Databricks, and Snowflake. Manage data modeling, quality, security, and analytics frameworks. Lead client accounts, mentor teams, and drive innovation to deliver data-driven business insights.

Leverage advanced analytics, data manipulation, visualization, statistical modeling, predictive analytics, and machine learning to generate client insights and recommendations. Apply Adobe Experience Cloud solutions to support business transformation and strategic decision-making. Build client relationships, manage and inspire teams, navigate complex engagements, uphold professional standards, and deliver quality outcomes while developing technical and consulting expertise.

Lead product analytics for Upsides consumer app: define KPIs and OKRs, design and analyze A/B tests, perform exploratory and root-cause analyses, forecast revenue impacts, build dashboards and data models, ensure robust instrumentation, and use AI tools to automate and scale experimentation and analytics workflows.

Supports the firm’s information governance program by managing electronic legal records and data throughout their lifecycle. Coordinates matter mobility, file transfers, retention, disposition, remediation, migration, audits, and compliance activities. Advises lawyers and staff on data storage, privacy, security, and records-management practices. Analyzes complex datasets, improves document-management-system adoption, leads projects, coordinates stakeholders, and recommends enhancements to global information governance processes.

Build and manage data ingestion, integration, transformation, modeling, and quality frameworks for federal financial management and IT programs. Analyze large datasets using SQL, Python, R, PySpark, and Databricks; develop predictive models and apply machine learning techniques. Ensure data governance and quality standards, define Databricks data quality metrics, support client meetings and documentation, and contribute to consulting and business development activities.

Leads the strategic direction of performance analytics and measurement for global enablement efforts. Owns the analytics roadmap, defines KPIs, develops AI-driven seller-readiness assessments, and partners with data engineering, sales, enablement, and technology teams. Translates complex analysis into executive-level insights, drives cross-functional alignment, and leads strategic measurement initiatives.

Analyze and document claim and encounter data, write complex SQL queries and reports, perform root-cause analysis, support system enhancements, execute test scripts, and collaborate with stakeholders to deliver data-driven solutions for healthcare claims/encounters.

Provides data analytics support for audits, inspections, investigations, fraud detection, and oversight activities. Responsibilities include data acquisition and cleansing, risk and anomaly analysis, forensic financial analysis, transaction tracing, entity resolution, dashboards, visualizations, reporting, data governance, and quality assurance. The role uses Power BI, Tableau, Python, Splunk, and Microsoft tools to present findings to technical and non-technical stakeholders.

Manages marketing technology, CRM data analytics, AI-enabled data enrichment, and data quality initiatives. Develops governance guardrails, standards, controls, and processes to maintain accurate data. Analyzes marketing and business development information to identify revenue and operational efficiency opportunities, creates recurring reports, collaborates with vendors and internal stakeholders, and implements tools that support strategic decision-making and demand generation.

Senior Addepar data engineer/analyst responsible for supporting and scaling Addepar integrations, building and maintaining data pipelines (Addepar↔Snowflake/Canoe/other platforms), diagnosing and resolving data quality issues, developing SQL-based reconciliations and automation, partnering with business and technology stakeholders, and supporting production operations, governance, testing, and documentation for wealth and asset management data.

Designs, builds, maintains, and troubleshoots SQL queries and data extracts for financial and operational reporting. Transforms source data into reliable datasets, automates recurring processes, validates and reconciles data, identifies quality issues, and supports integrations between systems and analytics platforms. The role also documents data flows and technical processes while supporting federal law enforcement clients.