Top Remote Data Engineer Jobs

The Data Engineer will develop data pipelines, support Agile teams, ensure data performance, and collaborate to implement complex requirements for federal customers.

The Data Engineer develops data pipelines, supports Agile teams, ensures data performance, advocates for lean practices, and collaborates across functions to deliver insights for federal customers.

The Data Engineer will develop data pipelines, ensure data reliability, and support process automation while collaborating within Agile teams.

The Data Engineer will develop data pipelines, support automation, and collaborate within an Agile team to manage complex data sets, ensuring performance and reliability in data processing.

Responsible for developing data pipelines, ensuring data extraction performance, and collaborating in an Agile team to provide data-driven solutions.

This role involves developing data pipelines, ensuring data performance, automating processes, and collaborating within Agile teams to meet complex data requirements.

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

As a Data Engineer, you will build and maintain data pipelines, ensure data quality, support ML workflows, and optimize query performance using various technologies.

The role involves designing and optimizing data pipelines in Snowflake, developing ETL workflows, collaborating on data integration, ensuring data security, and performance monitoring.

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

Forward-deployed senior data engineer who deploys, hardens, integrates, and operates a data platform (lakehouse, streaming, governance) in DoD environments. Build pipelines across classification boundaries, produce accreditation evidence (STIG/cATO/FIPS), run day-2 operations, train mission teams, and mentor junior FDEs while feeding field feedback into product improvements.

As a Data Engineer, you will build and maintain data pipelines, convert data into metrics, and operate the platform on AWS. Responsibilities include writing production code, processing data from APIs, and enhancing the orchestration layer using Dagster, while ensuring compliance in a HIPAA-regulated environment.

Design and deliver scalable data platforms and pipelines, enable data science teams, and implement best practices in automation and governance.

The Data Engineer will design and maintain data pipelines, enhance the data warehouse, support machine learning applications, and collaborate with various teams to leverage data effectively.

The Data Engineer I at Storable supports the design and maintenance of data pipelines, works with ETL processes, optimizes workflows, and collaborates with various teams to enhance data accessibility and reliability.

Manage delivery of complex data pipelines in a hands-on role, leading a team of data engineers to develop scalable data solutions and improve analytics capabilities.

Design, build, and maintain scalable batch and near-real-time data pipelines and data products using Databricks and Spark. Integrate internal/external sources, implement data models, ensure data quality, support BI (Sisense), CI/CD, and collaborate with analysts, scientists, and stakeholders to enable analytics and decision-making.

Build and maintain scalable data pipelines and integrations using Databricks and Azure. Transform and model large structured and unstructured datasets to support reporting, analytics, and operational needs. Implement data quality, monitoring, and governance; troubleshoot pipeline performance; collaborate with stakeholders and mentor junior engineers.

The Forward Deployed Data Engineer will manage AI-automated data platform migration projects, ensuring timely delivery and communication with clients while utilizing proprietary tools.

Design, build, and maintain scalable ETL pipelines and data architecture to ingest, validate, enrich, and integrate chemical and biological threat data. Implement metadata management, data cataloging, access controls aligned with NIST SP 800-171, and automate data quality checks. Collaborate with software and ML teams, support knowledge graph construction, resolve legacy data issues, and participate in Agile ceremonies and training.

Design and implement scalable data pipelines and orchestration on GCP to support AI/ML-driven mail intelligence. Build stream and batch processing, ensure data governance and quality, optimize workflows, create visualizations, and collaborate with US cross-functional teams to align technical strategy and recover from failures.

Design, develop, maintain, and optimize ADABAS database structures and data solutions. Support mainframe data processing (Natural, COBOL, JCL), perform migrations to modern platforms, tune performance, ensure data integrity/security, troubleshoot issues, and collaborate with developers, architects, and analysts on modernization, API/cloud integration, and data warehousing initiatives.

Design, build, and maintain Data Vault 2.0 data warehouse and Power BI solutions. Develop ETL pipelines, data models, reusable datasets, and data governance. Perform profiling, cleansing, migrations, and collaborate with infrastructure teams to optimize data delivery, automation, and reporting.

Own and maintain the companys data infrastructure and pipelines. Design, build, and monitor ETL/ELT workflows and data architecture; integrate SaaS sources; enforce data quality, standards, and governance; partner with stakeholders to deliver analytics-ready data and meet data availability SLAs.

Design, develop, and maintain ELT/ETL Snowflake data warehouse solutions; implement data standards, CI/CD, monitoring, and production support; collaborate with product, business, and vendors; mentor junior developers and improve data engineering practices.