Top Hybrid Data Engineering Jobs

Build and maintain data quality scripts and automated validation workflows, support large data migrations to modern platforms including public cloud, triage and repair data quality issues, prepare datasets for client-facing materials, and ensure access to databases for business intelligence tools.

As a Data Engineer II, you will build and maintain data pipelines, optimize performance, and collaborate with diverse stakeholders to enhance platform integration and data practices at Adyen.

Design, build, and maintain scalable data pipelines integrating diverse sources into analytics platforms. Own projects, standardize pipeline tooling, implement automated data tests, ensure security/PII handling, support on-call troubleshooting, and mentor team members to enable reliable, production-grade data delivery.

Design, develop, test, implement, and support cloud-based data solutions. Collaborate with Agile teams on full-stack and distributed systems, using Java/Scala/Python, RDBMS/NoSQL, data warehousing and streaming tools. Mentor engineers, perform unit tests and code reviews, and deliver performant, production-ready data platforms to support machine learning and customer-facing products.

Lead the development and implementation of automation techniques using AI and machine learning to improve life underwriting operations and processes.

The Lead Data Specialist will establish data architecture principles, develop solutions, and collaborate with teams to enhance ERP integrations and data management for the Cat Digital team.

Owner-operator for data processing automation: audit and redesign workflows, prototype scripting and low-code automations, configure client workflows, and translate messy private-markets data into clear technical requirements for the Data team.

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

The Senior Lead Analyst in Data Engineering is responsible for requirement gathering, building data enablement solutions, and overseeing ETL processes, while driving project delivery and mentoring team members.

Build data and AI-powered internal tools (meeting prep automation, portfolio benchmarking, diligence tooling) used by M13's investment team; produce clean, maintainable code, documentation, and collaborate with end users to iterate on production-ready systems.