Top Remote Data Engineer Jobs in Washington, DC

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.

Design and build data warehouse architecture, develop ETL/ELT pipelines, implement data governance, and partner with teams to improve data systems.

The Principal Data Engineer will lead data architecture initiatives, design scalable data systems, and oversee data standards across teams while ensuring high-quality data infrastructure and guiding engineering teams.

Design, build, and maintain scalable, reliable data pipelines and services. Write well-tested Python and SQL code, work with orchestration (Airflow), containers, and cloud infrastructure. Collaborate cross-functionally to deliver data products and improve development processes.

The Principal Data Engineer will design and implement enterprise data frameworks, mentor teams, and ensure data quality while collaborating with stakeholders.

The Data Engineer III will lead the development and maintenance of data infrastructure and tools, ensuring data integrity while driving strategic data initiatives.

Responsible for designing, developing, and maintaining databases and ETL systems, collaborating with stakeholders, and optimizing data integration processes.

As a Data Engineer, you'll design and optimize data pipelines, collaborate with teams for analytics and machine learning, and enforce data governance standards.

The Data Engineer will build scalable privacy-centric data frameworks, engineer data pipelines, and ensure compliance with privacy regulations at Netflix.

The Senior Data Engineer designs and maintains data pipelines, evaluates new technologies, mentors junior engineers, and ensures data system performance and reliability.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

The Data Engineer III will design and maintain data infrastructure, ensuring efficient data loading and compliance while mentoring junior engineers and collaborating with Analytics teams.

The Data Engineer is responsible for developing data infrastructure, building data pipelines, managing data quality, and integrating analytics tools to support design and project operations.

The Principal Data Engineer will lead data governance, architecture, and team development to unify data across systems while ensuring quality and compliance. Responsibilities include building data pipelines, establishing governance frameworks, and collaborating with cross-functional teams to drive data-driven insights and operational efficiencies.

Design, architect, and deliver services for Ensemble's products while collaborating with cross-functional teams and mentoring junior engineers.

Lead and mentor a data engineering team to design and operate scalable ETL/ELT pipelines and Snowflake data warehouse solutions using Python, DBT, Matillion, and AI tools; establish standards, ensure data quality and governance, and collaborate with analytics, product, and BI stakeholders to deliver production-ready data platforms.

As a Data Engineer, you'll design and implement data pipelines on Google Cloud, manage cloud infrastructure, ensure data quality, and enable analytics for marketing insights.

The Data Engineer will design and maintain data pipelines, optimize SQL queries, implement data workflows, and ensure data quality. The role demands collaborative problem-solving and technical communication skills to support analytics and business intelligence efforts.

Design, build, and optimize ETL pipelines and data workflows. Collaborate with teams to translate requirements into data solutions, ensuring data quality and efficiency.

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

Intern will gain hands-on experience in data engineering by working with technologies like Databricks, SQL, and Azure. Responsibilities include technical proficiency development and participation in AI projects.

The Lead Data Engineer will design and build scalable data pipelines on Databricks, develop ETL/ELT pipelines with PySpark, and mentor engineering teams for data transformation and analytics.

Design and develop scalable data pipelines using PySpark and Databricks, focusing on data ingestion, transformation, validation, and performance optimization.

The Principal Data Engineer will lead the Data Resolution team, focusing on complex data challenges using Spark, system architecture, and mentorship, to optimize graph data pipelines.