Senior Data Engineer - Data Architecture & Pipelines

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

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 scalable technical solutions. You will be part of a dedicated team creating datasets for analytic and data science workloads, and you will help model the Core Data Domain to support various access patterns and use‑cases.

Qualifications

• Bachelor's degree preferred/specialized training/relevant professional qualification.

Responsibilities

• Data Modeling & Architecture: Develop and optimize data models and schemas to support analytics, reporting, and machine learning requirements.
• Data Pipeline Development: Design and build ETL/ELT data pipelines to ingest, process, and transform large datasets from multiple sources.
• Performance Optimization: Implement best practices for performance tuning, partitioning, and clustering to optimize data queries and reduce costs.
• Data Quality & Governance: Establish and enforce data quality standards, data governance frameworks, and security policies for data storage and access.
• Data Integration & Transformation: Collaborate with data scientists and analysts to design data solutions that integrate with BI tools and machine learning models
• Documentation & Knowledge Sharing: Create comprehensive documentation for data pipelines, workflows, and processes. Share best practices and mentor junior data engineers.
• Design and architect data infrastructure analytical workloadsUnderstanding of data warehousing concepts, dimensional modeling, and building data marts.

Skills

SQL

Python

ETL pipelines

Azure

AWS

GCP

Data governance

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 scalable technical solutions. You will be part of a dedicated team creating datasets for analytic and data science workloads, and you will help model the Core Data Domain to support various access patterns and use‑cases.