Senior Data Engineer — Cloud Analytics & Pipelines

CVS Health Corporation; Washington (District of Columbia); Hybrid; USD 83,000 - 222,000; Full time

Job summary

CVS Health Corporation in Washington, DC is seeking a Senior Data Engineer to design and implement data pipelines powering analytical capabilities. This hands-on role requires expertise in data engineering best practices and translating business requirements into scalable technical solutions.

You will be part of a dedicated team creating datasets for analytic and data science workloads, modeling the Core Data Domain to support various access patterns and use-cases.

Qualifications

• Strong SQL proficiency and ability to develop complex queries.
• Excellent communication and collaboration with data scientists, analysts, and product owners.
• Bachelor's degree preferred or equivalent professional qualification.

Responsibilities

• Design and optimize data models and schemas to support analytics, reporting, and ML requirements.
• Build ETL/ELT pipelines to ingest, process, and transform large datasets from multiple sources.
• Tune performance through partitioning and clustering to optimize queries and reduce costs.
• Establish and enforce data quality standards, data governance, and security policies for data storage and access.
• Collaborate with data scientists and analysts to design data solutions for BI tools and ML models.
• Document data pipelines, workflows, and processes; mentor junior data engineers.

Skills

Strong SQL proficiency

Communication skills

Education

Bachelor's degree preferred

Tools

Python ETL

Cloud deployment (Azure AWS GCP)

Data governance practices

Job description

CVS Health Corporation in Washington, DC is seeking a Senior Data Engineer to design and implement data pipelines powering analytical capabilities. This hands-on role requires expertise in data engineering best practices and translating business requirements into scalable technical solutions.

You will be part of a dedicated team creating datasets for analytic and data science workloads, modeling the Core Data Domain to support various access patterns and use-cases.