Senior Data Engineer, Observability (Databricks Lakehouse)

CVS Health Corporation; Michigan; Hybrid; USD 93,000 - 222,000; Full time

Benefits offered by this job

Benefits package

Job summary

CVS Health is seeking a Senior Data Engineer, Observability Engineering to design, build, and operate scalable Databricks-based data pipelines powering observability and security analytics. You will collaborate with Security, Infrastructure, and Platform teams to evolve the enterprise data lakehouse and governance models.

The ideal candidate has 5+ years in big data engineering, extensive Databricks experience, and a strong focus on reliability, performance, and operational excellence.

Qualifications

• 5+ years building enterprise data pipelines with Python, Spark, PySpark, SQL.
• 5+ years designing and operating large-scale data pipelines across multiple sources.
• 4+ years with Databricks in production, including Delta Lake and Unity Catalog.
• 3+ years developing high-volume batch and streaming data solutions with data quality.
• 2+ years collaborating with engineering teams and communicating with stakeholders.

Responsibilities

• Design, build, deploy, and support scalable Databricks-based data pipelines and lakehouse solutions.
• Develop and optimize PySpark workloads, Structured Streaming, and bronze/silver/gold architectures.
• Onboard new data sources, establish governance standards, improve metadata management.
• Contribute to engineering standards, CI/CD practices, monitoring strategies, and platform optimization.
• Promote best practices for Databricks, Delta Lake, Unity Catalog, security controls, and cost-efficient data platform operations.

Skills

Python

Spark

PySpark

SQL

Data processing

Education

Bachelor’s degree

Tools

Databricks

Delta Lake

Unity Catalog

Databricks Asset Bundles

Job description

CVS Health is seeking a Senior Data Engineer, Observability Engineering to design, build, and operate scalable Databricks-based data pipelines powering observability and security analytics. You will collaborate with Security, Infrastructure, and Platform teams to evolve the enterprise data lakehouse and governance models.

The ideal candidate has 5+ years in big data engineering, extensive Databricks experience, and a strong focus on reliability, performance, and operational excellence.