Data Engineer

CVS Health

Closes in 3 days Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $64,890–$173,040 / yr
Posted: 7 days ago
Closes: Jun 19, 2026 (soon)

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $163k

This role $119k

$49k most similar roles pay here $216k

This role pays less than 90% of similar roles. Most pay $126,800–$198,987 — the shaded band above. At the midpoint, this role pays about $119k 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 143 open roles on FindRole.

Listed pay typically runs $118,450–$284,280 across 140 roles with salary data.

Most-posted roles

View all roles at CVS Health

At a glance

TL;DR · Data Engineer

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Data Engineer at a leading tech company, you will join a dynamic team focused on developing and maintaining robust ETL systems for data analysis and reporting. Your daily tasks include designing Airflow DAGs to execute complex data workflows, collaborating with other engineers to deploy machine learning models, and ensuring high availability of the system through monitoring and alerting mechanisms. You’ll leverage Python and SQL to build efficient data pipelines, enhance data quality, and support business intelligence platforms. Ideal candidates have 2+ years of experience in ETL systems, strong Python skills, proficiency in SQL dialects like Redshift or PostgreSQL, and a background in data modeling and governance. Familiarity with cloud computing services and workflow management tools such as Airflow is preferred.

Skills

Python SQL Airflow Redshift PostgreSQL ETL CI/CD AWS Azure GCP data modeling data governance data discovery tools

What you'll do

Design and manage ETL systems for data ingestion and transformation.
Write Airflow DAGs to execute tasks and deploy machine learning models.
Develop data products using agile practices including version control and testing.
Manage third-party data ingestion and export processes strategically.
Analyze, tune, troubleshoot, and support the data infrastructure for performance.

What we're looking for

2+ years of relevant data engineering experience
Strong Python and SQL (Redshift, PostgreSQL) skills
Experience designing and improving ETL systems
Knowledge of data modeling, access, and storage techniques
Proficiency in agile development practices (version control, testing)
Ability to translate business needs into technical requirements
Collaborative approach with strong partnership within teams

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