Staff Data Engineer

CVS Health

Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $106,605–$284,280 / yr
Posted: 7 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $178k

This role $195k

$85k most similar roles pay here $306k

This role pays more than 62% of similar roles. Most pay $139,537–$215,762 — the shaded band above. At the midpoint, this role pays about $195k versus about $178k for comparable roles.

Based on 240 similar postings.

Employer

About CVS Health

CVS Health is a leading American healthcare company operating retail pharmacies, pharmacy benefit management services, and a health insurance segment through Aetna, one of the nation''s largest health insurers. Industry: Healthcare & Pharmacy

CVS Health currently has 152 open roles on FindRole.

Listed pay typically runs $118,450–$260,590 across 149 roles with salary data.

Most-posted roles

View all roles at CVS Health

At a glance

TL;DR · Staff Data Engineer

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As a Staff Data Engineer at CVS Health, you will lead the evolution of data infrastructure by architecting petabyte-scale pipelines and building self-service platforms that modernize how data is ingested, accessed, and managed. You will design robust internal tools using React (TypeScript) for frontend interfaces and Python for backend services, while developing REST and gRPC APIs to serve Snowflake data layers efficiently. Additionally, you will implement GitOps practices with GitHub Actions and Argo/Kargo for CI/CD, and integrate AI tools like Cursor AI to optimize data engineering processes. With a focus on healthcare data spanning over 150 million individuals, your role involves extensive experience in Python, SQL, DBT, Snowflake, and React, along with proficiency in GitOps, API development, and big data architecture patterns such as Data Mesh.

Skills

Python SQL DBT Snowflake React TypeScript REST gRPC GitHub Actions Argo GitOps CI/CD Kafka SNS RabbitMQ Cursor AI Prometheus Grafana PostgreSQL MCPs

What you'll do

Architect and optimize petabyte-scale data pipelines using SQL, DBT, and Snowflake.
Develop internal React interfaces and Python backend services for automated data ingestion.
Build REST and gRPC APIs to interface between Snowflake data layer and consumer applications.
Implement CI/CD and GitOps practices for continuous delivery of data services.
Create self-service platforms enabling data owners to manage their pipelines autonomously.

What we're looking for

7+ years of experience in Data Engineering with Python as primary language.
7+ years of SQL and cloud data warehouse expertise (e.g., Snowflake).
7+ years building high-volume ETL/ELT pipelines and data modeling.
Experience with DBT, React for frontend applications, and RESTful APIs.
Proficiency in GitHub Actions, Argo/Kargo for GitOps-based deployments.
Understanding of big data design patterns like Data Lake, Data Mesh.

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