Top Hybrid Data Engineering Jobs

The Senior Data Engineer will build and scale data infrastructure, create data models, develop ingestion pipelines, and ensure data quality for drug development at Formation Bio.

The Senior Data Engineer will transform real-world data into analytics-ready datasets, build scalable pipelines, and conduct analyses to support scientific and business decisions, collaborating closely with data science teams.

The Distinguished Software Data Engineer role involves driving data architecture and engineering solutions, mentoring teams, and influencing technology adoption to enhance Capital One's data strategy.

This role involves designing data architecture and solutions, managing data pipelines, leading POCs, and collaborating across departments to implement data governance and quality practices.

Interns will assist with building dashboards, creating machine learning models, and modernizing data systems while collaborating with stakeholders across MetLife.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

The Principal Data Engineer will develop scalable data pipelines, manage data infrastructure across AWS, Databricks, and Snowflake, and enforce data quality and best practices.

As a Data Engineer at Edmunds, you will architect and maintain data platforms for analytics and AI/ML, ensuring scalable, reliable data processing and supporting cross-functional collaboration.

Lead a team of data engineers and analysts, manage cross-functional data projects, and integrate insights to improve product and customer value.

The Geospatial Data Engineer designs and implements data architectures and systems for intelligence analysis, supporting GEOINT analysts with automation and model creation.

The Senior Data Engineer will operationalize data governance by developing tools for data discovery, maintain data quality, and implement enterprise initiatives.

As an NLP Data Engineering Intern, you will transform text data into insights, design pipelines, and collaborate with teams to support AI applications.