Top Remote Senior Level Data Engineer Jobs

As a Senior Data Engineer at Arcadia, you will design and develop data pipeline connectors for healthcare data integration, manage technical documentation, participate in team projects, code reviews, and scrum ceremonies, while ensuring timely delivery of solutions and collaborating with various internal teams to enhance analytic capabilities.

The Data Center Selection Manager will enhance the quality and cost of colocation sites while managing vendor relations and executing contracts. Responsibilities include defining vendor strategy, conducting negotiations, working cross-functionally, and managing multiple projects effectively.

As a Principal Data Engineer, you will lead the technical direction of NBC News Digital's data infrastructure, design scalable data pipelines, collaborate with cross-functional teams, mentor junior engineers, and ensure data governance and quality for innovative solutions.

The Senior Machine Learning Engineer at Capital One will design, develop, and implement machine learning applications in an Agile environment. Responsibilities include collaborating with product and data teams, constructing optimized pipelines, and deploying models to ensure high performance and availability. The role also involves maintaining and monitoring models in production and upholding best practices in ML development.

As a Senior Data Engineer, you will transform operational data into analytical data, perform data analysis, write schema changes, and maintain ELT pipelines. You will champion a data-driven culture and interface with internal clients to understand their data needs, alongside troubleshooting data issues.

As a Staff Data Engineer, you will build scalable data infrastructure and design optimized data pipelines to support analytics and drive insights for mental health care. You will collaborate with cross-functional teams and improve data accessibility and quality to support informed decision-making.

The Senior Data Engineer will build and maintain data lakes and pipelines, improve data ingestion efficiency, and enhance self-serve data engineering capabilities. They will work with stakeholders to design and architect scalable solutions while ensuring high data quality and applying strong technical experience in data services management.