Senior Data Engineer - ETL Pipelines & Analytics (Cloud)

CVS Health; Alabama; On-site; USD 83,000 - 222,000; Full time

Job summary

CVS Health is seeking a Sr. Data Engineer in the United States to design and implement data pipelines powering analytical capabilities. This is a hands-on role requiring expertise in data engineering and translating business requirements into scalable technical solutions.

You will develop datasets for analytics and data science workloads and play a key role in modeling the Core Data Domain to support various access patterns and use cases.

Qualifications

• ~5+ years of applicable work experience.
• ~ Strong proficiency in SQL and experience in developing complex queries.
• ~ Experience in Python, specifically with ETL pipelines.
• ~ Experience deploying data pipelines in a cloud environment (Azure, AWS, GCP).
• ~ Knowledge of data governance best practices in a cloud environment.
• ~ Excellent communication and interpersonal skills, with the ability to collaborate effectively with data scientists, analysts, and product owners.

Responsibilities

• Data Modeling & Architecture: Develop and optimize data models to support analytics and ML.
• Data Pipeline Development: Design and build ETL/ELT pipelines from multiple sources.
• Performance Optimization: Tune, partition, and cluster data queries to reduce costs.
• Data Quality & Governance: Enforce data quality standards and security policies.
• Data Integration & Transformation: Collaborate with data scientists and analysts for BI and ML integration.
• Documentation & Knowledge Sharing: Create documentation and mentor junior engineers.
• Design and architect data infrastructure for analytical workloads; understand data warehousing concepts and data marts.

Skills

SQL

Python ETL

Cloud platforms

Data governance

Communication

Education

Bachelor's degree

Tools

Azure

AWS

GCP

Job description

CVS Health is seeking a Sr. Data Engineer in the United States to design and implement data pipelines powering analytical capabilities. This is a hands-on role requiring expertise in data engineering and translating business requirements into scalable technical solutions.

You will develop datasets for analytics and data science workloads and play a key role in modeling the Core Data Domain to support various access patterns and use cases.