Top Remote Data Engineer Jobs in Baltimore, MD

Design, build, and maintain scalable data pipelines and models; collaborate with analysts and data scientists to provision prepared datasets; implement data quality, governance and monitoring; recommend technologies; lead root-cause analysis, code reviews and testing; mentor teammates and support production data environments.

The Snowflake Data Engineer will work on data cleansing and harmonization, moving from legacy systems to SAP S4, focusing on ETL/ELT development and view creation.

This role involves designing, building, and maintaining data pipelines on Snowflake. Responsibilities include ensuring data quality and collaborating with stakeholders to deliver solutions.

The AWS Data Engineer will work on a data cleansing and harmonization project, focusing on AWS ETL design and development using various AWS services.

The Snowflake Data Engineer will design, build, and maintain data pipelines on Snowflake, optimizing performance and ensuring data quality while collaborating with stakeholders.

The Snowflake Data Engineer and Product Owner will manage the Snowflake data analytics project, collaborating with stakeholders, leading Agile practices, and ensuring quality deliverables through effective team coordination and backlog management.

Develop custom connectors on Airbyte for data ingestion from various platforms, ensuring accurate data integration and transformation. Collaborate with stakeholders and perform testing for reliability.

As a Principal Data Engineer, you'll design and maintain scalable data pipelines and frameworks using Azure technologies while collaborating with various teams to ensure data products support business decisions.

The Principal Data Engineer designs and maintains scalable data systems, evaluates new technologies, mentors junior engineers, and leads data engineering initiatives in agile environments.

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.

As a Data Engineer, you will develop solutions for customer-centric technology, ensuring platform integration and managing data architecture. Responsibilities include building data processes, maintaining data integrity, and collaborating cross-functionally to meet business challenges.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

The Data Engineer Consultant will design and implement scalable data solutions, advise clients on optimizing data environments, and develop ETL pipelines and data models to support business objectives.

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.

Design, build, and maintain end-to-end batch and streaming data pipelines; develop ETL/ELT workflows and modular Python code; write and optimize SQL; implement analytics data models; monitor data quality, troubleshoot failures, and document pipelines; collaborate with stakeholders and mentor teammates. Remote role for candidates based in Latin America.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

The Data Engineer at Anteriad will design, build, and optimize data pipelines, manage data integration processes, support analytics efforts, and collaborate with stakeholders to deliver scalable data solutions.

Design and optimize data pipelines, automate ingestion frameworks, and enhance data layers within GCP for healthcare analytics and reporting.

The Lead Data Engineer will design and optimize scalable data pipelines within GCP for healthcare analytics and reporting, lead automation efforts, and mentor junior engineers.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

The Data Engineer will build and maintain data platforms, deploy pipelines, monitor transformations, and collaborate with Data Scientists and DevOps.

The Principal Data Engineer will lead the design of data frameworks, mentor teams, implement MDM solutions, and ensure data quality across environments.