Senior Data Engineer: Architect & Build Scalable Data Pipelines

CVS Health Corporation; Maine; Hybrid; USD 133,000 - 222,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

Paid time off

Retirement savings options

Wellness programs

Bonus program

Job summary

CVS Health is seeking a Sr. Data Engineer to design and implement data pipelines powering analytical capabilities.

This hands-on role requires translating business requirements into technical solutions and contributing to the Core Data Domain to support various access patterns and use-cases. You will join a dedicated team creating datasets for analytic workloads, collaborating with data scientists and analysts to enable BI and ML workflows.

Qualifications

• 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 and architecture to support analytics and ML.
• Design and build ETL/ELT pipelines from multiple sources.
• Optimize performance through tuning, partitioning, and clustering.
• Establish data quality standards and data governance.
• Collaborate with data scientists to design integrated data solutions.
• Document pipelines and mentor junior engineers.
• Architect data infrastructure for analytical workloads and data marts.

Skills

SQL

Python ETL

Cloud deployments

Data governance

Communication

Team collaboration

Education

Bachelor's degree

Job description

CVS Health is seeking a Sr. Data Engineer to design and implement data pipelines powering analytical capabilities.

This hands-on role requires translating business requirements into technical solutions and contributing to the Core Data Domain to support various access patterns and use-cases. You will join a dedicated team creating datasets for analytic workloads, collaborating with data scientists and analysts to enable BI and ML workflows.