Top Senior Data Engineer Jobs in Washington, DC

As a Senior Associate in Data Engineering at PwC, you will design and implement data architecture strategies, analyze complex issues, mentor junior members, and build client relationships while ensuring adherence to project standards.

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

Own and modernize Upsides analytics data platform: migrate pipelines, reduce cost, improve governance, design reusable modeling/orchestration patterns, deliver domain-critical data products, lead cross-functional initiatives, mentor engineers, and support ML and product teams.

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

The Staff Data Engineer will lead design and implementation of analytics platforms and data products, collaborate cross-functionally, mentor engineers, and drive best practices at Upside.

The Senior IT Data Engineer will design and implement enterprise data architectures, develop scalable ETL/ELT pipelines, and support data-driven initiatives for the Federal Reserve Board.

The Data Engineer will design, build, and deploy scalable data solutions, optimize data flows, and implement ETL processes, leveraging various cloud platforms and technologies.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

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.

Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments.

Builds and maintains ETL and database pipeline architectures, automates data collection and validation, supports data modeling and reporting, collaborates with stakeholders and data science to integrate models, coaches junior staff, and implements governance and technical solutions for large datasets.

Design, build, and optimize end-to-end data pipelines and architectures on cloud infrastructure (AWS). Implement ETL/dataflow artifacts, support stakeholders, provide Tier 3 support, automate processes for scalability, and collaborate on product vision and roadmaps while supporting off-hours deployments as needed.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

Design, build, and maintain scalable ETL/ELT pipelines and data platforms using distributed tools and cloud services. Mentor cross-functional teams, oversee data architecture and modeling, process structured and unstructured data, and support analytics and mission-driven projects while meeting security clearance requirements.

The Data Engineer role involves developing and maintaining data pipelines for forecasting in commercial real estate, ensuring data integrity and supporting analytics teams.

Design, build, and deploy scalable data pipelines and validation for government production environments. Establish and maintain schemas, optimize SQL, handle messy/disparate data sources, work with large (100GB+) workflows, use Databricks/Spark/Python, and support ML/predictive solutions while mentoring teammates and engaging with clients. Active Secret Clearance required.

As a Senior Data Engineer at Jellyfish, you'll build and maintain data pipelines, optimize orchestration, automate CI/CD processes, and enhance data integration while ensuring high performance and reliability.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

The Data Engineer will develop data pipelines, manage complex data sets, and ensure data reliability while collaborating within an Agile/Scrum team.

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.

Build user-facing data products by transforming internal data into actionable metrics. Collaborate with platform teams and data scientists to prototype, validate, and prioritize data sources. Write requirements and proposals, engage in user research, and deliver performant Python/SQL-based data features using Databricks and Postgres.

Lead design and development of web UI and REST middleware within an Agile team. Define requirements and acceptance criteria, implement Java/Spring and Angular solutions, build CI/CD pipelines, work with Product Owner and testers, and produce/update design documentation.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.