Senior Data Engineer – Databricks Data Products

Edwards Lifesciences; Irvine (CA); On-site; USD 108,000 - 153,000; Full time

Job summary

Edwards Lifesciences in Irvine, CA is seeking a Senior Data Engineer to deliver enterprise data products on the Databricks Lakehouse Platform. You will transform raw data into reusable data assets that support analytics, reporting, and downstream applications across the enterprise.

This role emphasizes scalable pipelines, data governance, and collaboration with Data Science, Analytics, DevOps, and Platform Engineering teams to drive features from conception to production.

Qualifications

• Bachelor’s degree in a related field with 4+ years in Data Engineering/DevOps/Software Development
• Strong hands-on Databricks experience and SQL for data transformation
• Experience delivering end-to-end data products in a production environment

Responsibilities

• Apply hands-on expertise in Python, cloud technologies, Databricks, Apache Spark, SQL, and AI to build scalable data solutions
• Design, build, and maintain enterprise data products and ETL/ELT pipelines for batch and near-real-time processing
• Monitor, optimize Spark/Databricks workloads to improve performance and cost efficiency
• Collaborate cross-functionally with Data Science, Analytics, DevOps, Product, and Platform Engineering teams
• Troubleshoot and resolve data pipeline issues; enforce data quality via testing and CI/CD
• Ensure data privacy and governance compliance including PHI handling
• Contribute to architecture discussions and implement Lakehouse design patterns
• Perform other incidental duties as assigned

Skills

Databricks

Python

SQL

Spark

CI/CD

Cloud platforms

Education

Bachelor’s degree in a related field

Master’s degree

PhD

Tools

Databricks

Delta Lake

Git

Azure DevOps

GitHub Actions

Job description

Edwards Lifesciences in Irvine, CA is seeking a Senior Data Engineer to deliver enterprise data products on the Databricks Lakehouse Platform. You will transform raw data into reusable data assets that support analytics, reporting, and downstream applications across the enterprise.

This role emphasizes scalable pipelines, data governance, and collaboration with Data Science, Analytics, DevOps, and Platform Engineering teams to drive features from conception to production.