Top Hybrid Data Engineering Jobs

The Lead Data Migration Specialist will enhance data processes for client onboarding using Excel, SQL, and AI, ensuring accuracy and efficiency.

The role involves building and improving WHOOP's data platform infrastructure, ensuring reliability and efficiency, and driving best practices across engineering and data workflows.

The role involves building and scaling a scientific model platform at Benchling, integrating various AI models, and collaborating with users to optimize usage in biotech R&D.

As a Staff Analytics Engineer, you'll lead analytics architecture, ensure data quality, collaborate with stakeholders, and drive AI-powered data insights for business decision-making.

The Data Engineer will design and evolve data governance platforms, implement secure data solutions, and mentor junior team members. Responsibilities also include enhancing system quality through automation, collaborating within agile teams, and applying best practices in coding and testing for analytics and data science.

As a Senior Data Engineer, you will manage data integration, optimize performance, mentor junior engineers, and collaborate with product teams on innovative solutions in healthcare data modeling.

As a Lead Data Engineer, you will design scalable data platforms, optimizing pipelines, defining data models, and guiding data integration while collaborating with cross-functional stakeholders to align strategies with business goals.

As a Data Engineer, you'll design, build, and maintain ETL/ELT pipelines, develop data infrastructure, collaborate with BI teams, and optimize data models for reporting.

Lead the design and implementation of enterprise-scale Knowledge Graphs and Semantic AI solutions, integrating graph intelligence and Generative AI. Manage cross-functional teams in data architecture and governance.

Design and implement ETL pipelines, optimize data systems, build data warehouses, and develop AI/ML models for data solutions. Collaborate with teams to deliver data-driven products and ensure data quality and governance.