Top Hybrid Data Engineering Jobs

The Senior Data Center Administrator oversees operations, including inventory management, vendor coordination, capacity planning, and safety compliance in the data center.

The Senior Data Center Administrator is responsible for data center operations including inventory management, logistics, vendor coordination, and capacity planning. The role requires technical expertise and strong communication skills to ensure efficient data center environments across multiple locations.

The Senior Enterprise Applications Engineer designs and maintains data architecture and pipelines, supports financial reporting, manages projects, and mentors junior members while utilizing business intelligence tools and emerging technologies.

Lead Data Engineer responsible for designing, building, testing, and supporting cloud-based data platforms and streaming solutions. Collaborate across Agile teams, mentor engineers, apply big data and distributed computing tools, and deliver performant, production-grade data services that support product and ML use cases.

Summer internship on the Data & Analytics Platform team building automation, model prototypes, and platform features. Work with engineers to write, test, and deploy code, partner with internal customers to prototype ML and generative workflows, and participate in design discussions and code reviews in an agile environment.

Lead Analytics Engineer responsible for data modeling, transformation, pipeline orchestration, quality governance, and empowering data-driven decisions across the organization.

The Senior Analytics Engineer will design and maintain ELT pipelines, manage data layer for CX, and partner with teams to transform data into actionable insights.

The Data Analytics Engineer will develop data models, perform data wrangling, and create dashboards to drive insights for business decisions at Bose Corporation.

The role involves implementing mortgage prepayment models into a financial analytics library using C++, requiring collaboration across teams and adherence to software engineering practices.

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.

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.

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