Top Senior Level Data Engineer Jobs

The Principal Cloud Database Engineer designs, implements, and manages cloud-based database solutions, ensuring high performance, data integrity, and security. Responsibilities include database administration, performance tuning, automation, and collaboration with development and infrastructure teams. This role also involves capacity planning, monitoring, and compliance with data protection regulations while leading technical initiatives and supporting operational excellence.

The Senior Data Science Engineer will develop, test, and productionize machine learning models, optimize data delivery processes, and build infrastructure for data extraction and analysis. Responsibilities include model performance testing, algorithm improvements, and collaboration with cross-functional teams.

The Senior Data Engineer at CodaMetrix focuses on maintaining and optimizing the data platform and analytics architecture. Responsibilities include creating and managing data pipelines, collaborating with multiple teams for data infrastructure needs, and enhancing data accessibility and performance to support analytical initiatives and AI-driven products.

As a Lead Data Engineer at Lumos, you will architect and maintain data pipelines to support AI products and analytics, focusing on reliability, scalability, and integration of various data sources to drive business insights.

The Senior Principal Data Engineer at Northrop Grumman will design, develop, and deploy scalable data architecture solutions while maintaining databases. Responsibilities include data mapping, ETL processes, query development, and collaborating with stakeholders to meet needs and objectives.

As a Senior DBA at the Wikimedia Foundation, you will ensure the health and performance of database systems, manage troubleshooting and maintenance, handle database version upgrades, optimize query performance, design database schema, participate in incident response, and contribute to high availability setups.

As a Lead Data Engineer, you will design and architect cloud data lakes, implement tabular data formats, develop scalable data platforms, and collaborate with AI teams to enable data pipelines for model training and inference while ensuring data quality and governance.