Senior Data Engineer

CVS Health

Confirmed live today High trust

Closes in 7 days Remote

Quick summary

Work type: Remote
Location: ILArkansasIdahoTexasGeorgiaMontanaIowaWisconsinOregonWashingtonNew York, NYDistrict of ColumbiaConnecticutNebraskaRhode IslandTennesseeKentuckyOhioWest VirginiaMarylandMassachusettsSouth CarolinaMissouriUtahArizonaSouth DakotaPennsylvaniaNew HampshireVermontMinnesotaNew MexicoMichiganCaliforniaMaineNorth DakotaKansasIndianaNew JerseyNevadaLouisianaMississippiOklahomaAlabamaVirginiaNorth CarolinaColoradoFloridaWyomingDelaware
Salary: $83,430–$222,480 / yr
Employment: Full-time
Posted: 2 days ago
Freshness: Confirmed live today
Closes: Oct 9, 2026 (soon)
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $167k

This role $153k

$67k most similar roles pay here $239k

This role pays less than 62% of similar roles. Most pay $135,187–$198,631 — the shaded band above. At the midpoint, this role pays about $153k versus about $167k 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 81 open roles on FindRole.

Listed pay typically runs $106,605–$260,590 across 80 roles with salary data.

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View all roles at CVS Health

At a glance

TL;DR · Senior Data Engineer

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As a Senior Data Engineer, you will join a dedicated team focused on creating datasets for analytic and data science workloads while modeling the Core Data Domain to support various access patterns. You will be responsible for designing and building ETL/ELT pipelines to ingest and transform large datasets from multiple sources, optimizing performance through partitioning and clustering, and establishing data quality standards and governance frameworks. The role requires developing complex SQL queries and utilizing Python for pipeline development within cloud environments like Azure, AWS, or GCP. You will collaborate with data scientists and analysts to integrate solutions with BI tools and machine learning models. Specialized experience includes working with healthcare data, specifically Tuva or OMOP Models, and managing machine learning flows on GCP to solve technical challenges in the health domain.

What does a Data Engineer earn in California?

Median $187556 from 35 postings across 18 companies.

See salary data

Skills

SQL Python ETL ELT Data Modeling Data Warehousing Dimensional Modeling Azure AWS GCP Machine Learning Data Governance Data Pipelines Tuva OMOP Models

What you'll do

Design and optimize data models and schemas to support analytics, reporting, and machine learning requirements.
Build ETL/ELT pipelines to ingest, process, and transform large datasets from multiple sources.
Implement performance tuning, partitioning, and clustering to optimize queries and reduce costs.
Establish and enforce data quality standards, governance frameworks, and security policies for storage and access.
Create technical solutions that integrate data with BI tools and machine learning models.
Architect data infrastructure and manage the Core Data Domain to support various use cases.
Create comprehensive documentation for pipelines and mentor junior data engineers on best practices.

What we're looking for

Strong proficiency in SQL and experience developing complex queries.
Experience in Python, specifically with ETL pipelines.
Experience deploying data pipelines in a cloud environment (Azure, AWS, or GCP).
Knowledge of data governance best practices in a cloud environment.
Excellent communication and interpersonal skills to collaborate with cross-functional teams.
Experience with machine learning flows on GCP (preferred).
Experience working with healthcare data, such as Tuva or OMOP Models (preferred).
Bachelor's degree, specialized training, or relevant professional qualification (preferred).