Top Data Engineer Jobs in Washington, DC

The Senior Data Engineer will design and maintain data infrastructures, support analytics, and collaborate with stakeholders to improve data quality and governance while utilizing DBT and AWS tools.

Provide pre-sales technical leadership for field sales: design and validate data management and analytics solutions, lead POCs/demos, perform systems integration, and advise on cloud data platforms, unstructured data processing, RAG/GenAI, ETL/ELT, governance, BI and ML workflows.

The Lead Data Engineer drives enterprise-scale data solutions, oversees project scoping, and leads a team, ensuring best practices in data engineering.

The Senior Data Engineer will design, construct, test, and maintain architectures including databases and large-scale processing systems.

As a Senior Data Engineer, you will implement and optimize Google Analytics systems for accurate user behavior measurement across platforms, ensuring scalability and data accuracy.

Implement and enforce data governance, manage data cataloging and metadata, facilitate Atlan adoption, align data models with analytics needs, manage controls and audits, mentor junior staff, and resolve data quality issues while collaborating with business and engineering teams.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Ensure timely, high-quality data conversions from legacy systems to new platforms. Work with Implementation Specialists and Project Managers to execute conversion tasks, validate data integrity, troubleshoot issues, support deployments, and assist scheduling and customer communications.

The Senior Data Engineer will design and optimize data infrastructures and pipelines, lead projects, mentor juniors, and enforce best practices.

Lead and scale the data analytics function, manage a distributed analytics team, deliver actionable insights, and oversee analytics projects.

Design and build Spark ETL pipelines on an AWS data platform, collaborate with stakeholders to deliver reliable large-scale data products, optimize and maintain data infrastructure, ensure data quality/governance, and manage platform operations and incident response.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

Lead design, build, and optimization of Sezzle's large-scale data warehousing and pipelines. Own data infrastructure KPIs/SLAs, improve Redshift performance, evolve the data stack, implement ETL/ELT workflows, and partner with cross-functional teams to deliver reliable, scalable datasets.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

As a Senior Data Engineer, you will design and maintain scalable data pipelines, focusing on architecture, ingestion, storage, and analytics on GCP. You'll collaborate with stakeholders and optimize data structures for performance while ensuring adherence to data governance and compliance standards.

The Senior Data Engineer will focus on Data Modeling, utilizing SQL, Snowflake, and Apache Airflow to develop efficient data models and deliver data products.

Design, build, and maintain production data pipelines and tooling (CI/CD, testing, validation) using Snowflake, dbt, and orchestration tools. Model, transform, document, and optimize data to produce reliable curated datasets for analytics and solutions, enforce engineering best practices, and mentor teammates while ensuring scalability, observability, and data integrity.

Design and optimize BI semantic models and analytics workflows using PowerBI and Tabular Editor; build and transform large-scale datasets in BigQuery with dbt; implement CI/CD and deployment via GitHub and Azure DevOps; collaborate with stakeholders to deliver actionable visualizations and integrate Agentic AI into analytics pipelines.

Lead design, build, and support of cloud-based ETL, data warehousing, and reporting solutions. Develop/optimize ETL pipelines, data models, and queries; deploy containerized services on Kubernetes; automate workflows; mentor teammates; collaborate with architects, data scientists, and stakeholders to deliver scalable analytics and reporting products.

Architect, build, and maintain scalable ELT data pipelines and analytics-ready data marts. Lead dbt modeling, ensure data quality, CI/CD, and documentation. Partner with stakeholders, mentor junior engineers, evaluate tooling (reverse ETL), and drive long-term data platform strategy.

Design, build, and maintain production data pipelines and the unified data model using Snowflake, dbt, and orchestration tools. Optimize, test, document, and monitor ELT workflows, enforce engineering best practices, mentor teammates, and deliver trustworthy data products for analytics and business decisions.

As a Senior Data Engineer at EverHealth, you will design and maintain data pipelines, enhance warehouse infrastructure, and ensure data quality to support reporting and analytics for healthcare products.

The Senior Data Engineer will design and build data pipelines on Azure Databricks, ensuring data security and governance while collaborating with clients and vendors on projects.

Design, build, and scale data pipelines and integrations for the TDX platform. Implement REST API integrations, ingest and unify customer data, optimize pipelines for performance and quality, ensure data security and governance, and collaborate with Product, Data Science, and customer teams to deliver reliable analytics-ready data.