Top Hybrid Data Engineering Jobs

The EDI Analyst designs, implements, and supports EDI systems, manages integrations, and resolves issues, enhancing data exchange efficiency.

The Lead Data Engineer designs and develops technical solutions, collaborates with Agile teams, and utilizes big data technologies, cloud computing, and full-stack development to drive digital transformation at Capital One.

Lead the design of scalable data architectures, optimize data processing workloads, and mentor talent while promoting modern technologies and engineering excellence.

The Data Engineer will design and build scalable data systems, contribute to the architecture of the data platform, and collaborate with AI/ML engineers to enhance automation and intelligence in Canoe's systems.

The Data Migration Engineer migrates customer data into SaaS products, ensuring data quality and business continuity while collaborating with teams and managing customer requirements.

As a Senior Associate, you will assist clients in cloud data strategies, leveraging analytics, and aligning data architecture with business needs within a professional services framework.

The Sr. Business Intelligence Data Engineer designs data pipelines, optimizes ETL processes, and ensures data integrity in a Databricks environment while collaborating with cross-functional teams.

The Cloud Data Architect will design scalable data architectures for SaaS solutions, set data standards, collaborate with engineering, and ensure data governance and optimization. Requires advanced SQL and cloud platform proficiency.

The Analytics Engineer will enhance data assets, develop data models, optimize BI infrastructure, manage cross-functional partnerships, and ensure data quality through anomaly detection and documentation.

The SOX Data Analytics & AI Manager will develop and implement data analytics and automation solutions for SOX compliance, lead a team, and collaborate across functions to enhance efficiency in internal controls.

As a Data Engineer II, you will build and optimize data pipelines in Databricks, ensure high-quality data delivery, and support generative AI applications. You will collaborate with data scientists and AI engineers to provide reliable data infrastructures and meet business needs.