Top Hybrid Data Engineering Jobs

Lead analytics work for card products by building data solutions, dashboards, and data quality tooling. Partner with business stakeholders to translate needs into insights, leverage Snowflake and scripting (Python/R/Spark/SQL), and enforce data governance and access controls.

Lead design, build, and maintain scalable data pipelines and warehouses. Drive technical roadmap, mentor engineers, implement data quality/testing/monitoring, optimize performance and cost, and collaborate cross-functionally to ensure reliable data for BI, ML, and applications.

Lead and grow a data engineering team that designs, builds, tests, and operates large-scale data pipelines and warehouses. Partner cross-functionally to translate requirements, ensure data quality, observability, SLAs, security, and governance, and drive automation and performance for analytics, ML, and product use cases.

The Data Engineer will build datasets and pipelines for marketing and sales reporting, collaborating with various teams to support data needs and ensure scalable solutions.

Build and own end-to-end sales data pipelines and curated marts in Snowflake/dbt; implement monitoring, tests, and governance; run reverse-ETL to operational systems; partner with Sales, Ops, Finance, and People to deliver production-ready analytics products.

The Associate Data Engineering role focuses on building data solutions and pipelines, learning from senior engineers, and participating in a structured tech program.

Design, build, and maintain cloud-based data pipelines and products (batch and streaming). Develop microservices, orchestration, and feature stores in AWS. Partner with stakeholders, automate ETL, enable self-service analytics, and mentor junior engineers.

As a Staff Data Engineer, you develop data products, design data for analytics, and support Precision Ag business through data insights and tools. You will harmonize data, implement data pipelines, and lead teams on complex projects, ensuring efficient and impactful solutions for agriculture.

Lead development of scalable data solutions that integrate deep learning. Manage data quality, metadata, and facilitate cross-functional data initiatives for business value.

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

The Senior Snowflake Data Engineer designs and optimizes Snowflake architecture and pipelines, ensuring data governance and performance across Marketing and Sales teams.