Senior Data Engineer - Cloud & On-Prem Data Warehousing

Hispanic Alliance for Career Enhancement; Springfield (IL); On-site; USD 65,000 - 173,000; Full time

Job summary

CVS Health is seeking a Senior Data Engineer to deliver modern data solutions in a fast-paced, agile environment. You will design, integrate, and implement data solutions on-premise while supporting migrations to the cloud, focusing on payer data into our Data Warehouse.

The ideal candidate has extensive experience with SQL, Python, PySpark, and dimensional modeling, working across engineering, analytics, and product teams to drive reliable data pipelines and scalable warehousing.

Qualifications

• 4+ years of experience with SQL and relational databases.
• 2+ years in Cloud Data Engineering Platforms (AWS, GCP, Azure, Databricks, Snowflake, etc.).
• 2+ years in on-prem Data Engineering Platforms (SQL Server, Oracle, Teradata).
• Programming in SQL, Python, and PySpark for cloud and on‑prem data warehousing.
• Experience with dimensional data modeling and data warehousing.
• Hands-on experience troubleshooting data issues.
• Willingness to own process improvements in a fast-paced, collaborative environment.
• Excellent oral and written communication skills.

Responsibilities

• Deliver high-quality data solutions in collaboration with engineering, analysts, data scientists, and product teams.
• Design, integrate, and implement on-prem and cloud migration strategies.
• Support migrations of workloads to the cloud and maintain data warehouse integrity.
• Process payer files into CVS Health's Data Warehouse.

Skills

SQL

Cloud platforms

Python

PySpark

Dimensional modeling

Data warehousing

Troubleshooting

Communication

Education

Bachelor's degree in CS/Engineering

Tools

SQL Server

Oracle

Teradata

Job description

CVS Health is seeking a Senior Data Engineer to deliver modern data solutions in a fast-paced, agile environment. You will design, integrate, and implement data solutions on-premise while supporting migrations to the cloud, focusing on payer data into our Data Warehouse.

The ideal candidate has extensive experience with SQL, Python, PySpark, and dimensional modeling, working across engineering, analytics, and product teams to drive reliable data pipelines and scalable warehousing.