onsite
Data Engineer - Edwards Lifesciences
Data Engineer
Data Engineer responsible for designing, building, and maintaining enterprise‑scale data products on the Databricks Lakehouse platform, leveraging Spark, Python, and SQL to enable analytics for heart‑failure management solutions.
About the role
Key Responsibilities
- Design, develop, and deploy scalable data pipelines on the Databricks Lakehouse platform using Apache Spark and Python.
- Implement robust ETL processes to ingest, transform, and store clinical and device data from multiple sources.
- Collaborate with data scientists, product owners, and clinicians to deliver high‑quality data products that support analytics and decision‑making.
- Optimize query performance and data models in SQL to ensure low‑latency access for downstream applications.
- Maintain data governance, security, and compliance standards across the data lakehouse environment.
Requirements
- 3+ years of hands‑on experience building data solutions on Databricks or similar lakehouse platforms.
- Proficiency in Apache Spark (PySpark or Scala) and strong Python programming skills.
- Deep knowledge of SQL and relational/NoSQL data modeling for large‑scale analytics.
- Experience designing and operating ETL pipelines, data warehousing, and data lake architectures.
- Solid understanding of data security, governance, and best practices in a regulated (e.g., healthcare) environment.
Skills
databricksapache sparkpythonsql