Data Engineer

CVS Health

Remote Hybrid

Quick summary

Work type: Remote
Location: Wellesley, MA · New York, NY · Hartford, CT
Salary: $79,310–$173,040 / yr
Posted: 3 days ago
Closes: Jun 15, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $163k

This role $126k

$65k most similar roles pay here $214k

This role pays less than 88% of similar roles. Most pay $126,800–$199,850 — the shaded band above. At the midpoint, this role pays about $126k versus about $163k 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 156 open roles on FindRole.

Listed pay typically runs $118,450–$260,590 across 152 roles with salary data.

Most-posted roles

View all roles at CVS Health

At a glance

TL;DR · Data Engineer

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As a Data Engineer at CVS Health, you will join a dynamic team responsible for building and maintaining robust data pipelines to support the company’s diverse business units. Your daily tasks include designing and optimizing analytical models in BigQuery, developing integrations with external systems using GCP tools like Dataflow or Cloud Functions, and setting up automated CI/CD pipelines with Cloud Build or Jenkins. You will also ensure observability through Cloud Monitoring and Logging. The role requires expertise in SQL, Python, data warehousing, ETL processes, and cloud architecture on platforms such as Google Cloud Platform (GCP). Additionally, you should have experience with Kubernetes for containerized environments, real-time streaming technologies like Kafka or Spark Streaming, and strong collaboration skills to manage stakeholder relationships effectively.

Skills

BigQuery Python GCP Kubernetes CI/CD Cloud Build GitHub Actions Jenkins Cloud Monitoring Cloud Logging Error Reporting SQL NoSQL ETL ELT Data warehouses Kafka Spark Streaming Git Bash shell scripts UNIX utilities Waterfall Agile API development schema design dimensional data modeling

What you'll do

Build and optimize analytical data models in BigQuery for performance and cost efficiency.
Develop integrations with external systems using GCP-native tools or hybrid approaches.
Implement automated CI/CD pipelines for deploying data pipeline code and workflows.
Set up observability using Cloud Monitoring, Logging, and Error Reporting to ensure reliability.
Design and maintain high-volume data pipelines within a major cloud platform like GCP.

What we're looking for

1+ years of experience with SQL and NoSQL databases
1+ years of hands-on experience building data pipelines in GCP
1+ year of expertise in ETL/ELT processes and query optimization
Experience deploying applications on Kubernetes or similar containerized environments
Proficiency in Python and other scripting languages for data engineering tasks
Knowledge of BigQuery, including partitioning, clustering, and materialized views
Strong collaboration skills with stakeholders and cross-functional teams

Hybrid

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