Senior Data Engineer – Cloud & On-Prem Data Warehouse

Quest Oracle Community; Des Moines (IA); Hybrid; USD 65,000 - 173,000; Full time

Job summary

CVS Health is seeking a Senior Data Engineer to design, integrate, and implement modern data solutions. You will work with engineering, analysts, data scientists and product teams in an agile environment to manage on‑prem data warehouses and cloud migrations.

You will apply deep SQL, Python, and PySpark skills, build dimensional models, troubleshoot data issues, and drive performance improvements in a fast‑paced healthcare data environment.

Qualifications

• 4+ years of experience with SQL and relational databases.
• 2+ years in Cloud Data Engineering platforms (AWS, GCP, Azure, Databricks, Snowflake).
• 2+ years in on-prem data engineering platforms (SQL Server, Oracle, Teradata).
• Programming in SQL, Python, PySpark for cloud and on‑prem warehousing.
• Experience with dimensional data modeling and data warehousing.
• Ability to troubleshoot data issues and optimize performance.
• Strong communication skills and collaborative mindset.

Responsibilities

• Design, develop, and deliver modern data solutions.
• Collaborate with engineering, analysts, data scientists, and product teams.
• Support migrations of workloads from on‑prem to the cloud.
• Work within an agile environment to implement data warehousing services.

Skills

SQL

Python

PySpark

Cloud platforms

On-prem data warehousing

Dimensional modeling

Data troubleshooting

Performance optimization

Communication

Education

Bachelor's degree in Computer Science / Engineering

Tools

AWS

GCP

Azure

Databricks

Snowflake

Microsoft SQL Server

Oracle

Job description

CVS Health is seeking a Senior Data Engineer to design, integrate, and implement modern data solutions. You will work with engineering, analysts, data scientists and product teams in an agile environment to manage on‑prem data warehouses and cloud migrations.

You will apply deep SQL, Python, and PySpark skills, build dimensional models, troubleshoot data issues, and drive performance improvements in a fast‑paced healthcare data environment.