Senior Data Engineer: Cloud Pipelines for Health Analytics

CVS Health Corporation; North Carolina; Hybrid; USD 83,000 - 222,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

Paid time off

Retirement savings

Wellness programs

Job summary

CVS Health Corporation is seeking a Sr. Data Engineer to design and implement data pipelines powering analytical capabilities. This hands-on role requires translating business requirements into robust data engineering solutions.

You will help model the Core Data Domain and collaborate with data scientists to support BI and ML workloads. A strong foundation in SQL, Python ETL, and cloud platforms is essential.

Qualifications

• Strong SQL and the ability to write complex queries.
• Proficiency in Python for 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 collaboration with data scientists, analysts, and product owners.

Responsibilities

• Data Modeling & Architecture: develop data models and schemas for analytics and ML.
• Data Pipeline Development: design and build ETL/ELT pipelines from multiple sources.
• Performance Optimization: tune queries, partitioning, and clustering to reduce costs.
• Data Quality & Governance: enforce data quality standards and security policies.
• Data Integration & Transformation: work with BI tools and ML models.
• Documentation & Knowledge Sharing: create docs and mentor juniors.
• Design and architect data infrastructure for analytical workloads and data marts.

Skills

SQL

Python

Cloud (Azure/AWS/GCP)

Data governance

Communication

Education

Bachelor's degree

Job description

CVS Health Corporation is seeking a Sr. Data Engineer to design and implement data pipelines powering analytical capabilities. This hands-on role requires translating business requirements into robust data engineering solutions.

You will help model the Core Data Domain and collaborate with data scientists to support BI and ML workloads. A strong foundation in SQL, Python ETL, and cloud platforms is essential.