Senior Data Engineer: ETL & Analytics Pipelines

CVS Health; Oklahoma City (OK); On-site; USD 83,000 - 222,000; Full time

Benefits offered by this job

Medical, dental, and vision coverage

Paid time off

Retirement savings options

Wellness programs

Job summary

CVS Health in Oklahoma City seeks a Sr. Data Engineer to design and implement data pipelines powering analytics and data science workloads. You will model the Core Data Domain to support diverse access patterns and use-cases.

This hands-on role requires strong SQL, Python ETL, and cloud experience (Azure/AWS/GCP), collaboration with data scientists, and a focus on data quality, governance, and scalable architectures.

Qualifications

• 5+ years of data engineering experience.
• Strong SQL skills with complex queries.
• Python experience for ETL pipelines.
• Cloud deployment of data pipelines (Azure/AWS/GCP).
• Knowledge of data governance in cloud environments.
• Excellent communication and collaboration with data scientists and analysts.

Responsibilities

• Data Modeling & Architecture: develop data models and schemas for analytics, reporting, and ML.
• Data Pipeline Development: build ETL/ELT pipelines across multiple sources.
• Performance Optimization: tune queries, partitioning and clustering to reduce costs.
• Data Quality & Governance: enforce data quality, governance, and security policies.
• Data Integration & Transformation: collaborate with data scientists/analysts to BI/ML integrations.
• Documentation & Knowledge Sharing: create docs and mentor junior engineers.
• Architect data infrastructure for analytical workloads with warehousing concepts and data marts.

Skills

SQL

Python ETL

Cloud data pipelines

Data modeling

Data governance

Education

Bachelor's degree

Tools

Azure

AWS

GCP

Job description

CVS Health in Oklahoma City seeks a Sr. Data Engineer to design and implement data pipelines powering analytics and data science workloads. You will model the Core Data Domain to support diverse access patterns and use-cases.

This hands-on role requires strong SQL, Python ETL, and cloud experience (Azure/AWS/GCP), collaboration with data scientists, and a focus on data quality, governance, and scalable architectures.