Top Remote Data Engineer Jobs in Baltimore, MD

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

As a Data Engineer II, you will build and optimize data pipelines in Databricks, ensure high-quality data delivery, and support generative AI applications. You will collaborate with data scientists and AI engineers to provide reliable data infrastructures and meet business needs.

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

As a Data Engineer II, you'll build and maintain data pipelines, develop cloud-based infrastructure, and ensure robust data governance, partnering across teams to support data-driven analytics.

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.

The Data Engineer I is responsible for building reliable ELT/ETL pipelines, implementing data quality checks, and optimizing data models using dbt, while collaborating with stakeholders to ensure data reliability and consistency.

The Data Engineer will design, build, and maintain analytics-ready Data Marts, create resilient data pipelines, and ensure data integrity, working closely with analytics teams to deliver reliable datasets.

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 Senior Data Engineer, you will design data pipelines, manage databases, optimize data workflows, ensure data integrity, and collaborate with cross-functional teams on data-driven solutions.

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.

Migrate HiveQL and Python workflows from CDSW to Databricks, design and maintain ETL pipelines and databases, optimize data workflows on cloud platforms (AWS/Databricks), implement CI/CD, and collaborate with analytics teams to ensure scalable, high-quality data delivery supporting DoD stakeholders.

The role involves writing and deploying scripts for data collection, transforming data sets, diagnosing bugs, and collaborating with other engineers using agile principles.

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

The Senior Data Engineer designs and maintains data pipelines, ensures data quality, and supports advanced analytics for U.S. Naval Aviation. They oversee data engineering practices and contribute to enterprise-scale architecture initiatives.

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.