Data Engineering at Aetna
Roles, Comp & Culture
An L6 staff data engineer at Aetna sits around $193K total comp from 13 verified salary datapoints. The primary Data Engineering tech consists of Hadoop, GCP and AWS, according to current job listings. Aetna pays data engineers in line with other Healthcare companies. Reviews put them at 3.4 on Glassdoor, toward the bottom of the pack. Employee sentiment at Aetna reads neutral and employee happiness is trending up over the past year. Layoff risk scores low for the next 30 days. 78 data engineering roles are open right now.
Aetna data engineer compensation
Each level's figure is the median of individual Aetna offers at that level, so it reflects a typical outcome rather than an average pulled up by a few large packages. Total comp counts base salary plus equity and bonus annualized over the vest, and the range shown is the middle half of offers, with the top and bottom quarters trimmed off.
Aetna employee sentiment, tracked weekly
Employee happiness for data engineers over the past year, so you can see which direction it is moving, not just where it sits today.
Aetna's employer bargain is steadier than it is exciting. Pay at {{in line with}} other Healthcare companies, with $193K at L6 and $130K at entry, puts compensation in a mid-market range for the industry. The Glassdoor rating of 3.4 sits toward the bottom of the pack, and Blind sentiment is mixed, which together point to a workplace where some engineers find the stability and scope genuinely satisfying while others chafe against the pace of change inside a large, heavily regulated enterprise. Happiness is neutral and trending up, which is about what you'd expect from a post-merger environment still rationalizing its technology stack. The trade is real: you get durable employment, a large and complex data domain, and accumulated institutional knowledge on healthcare pipelines; you give up the velocity and tooling modernity you'd find at a pure-play tech company.
The hiring signal is the clearest positive indicator right now. 78 open data engineering roles across 11 cities, with Irving as the primary market, which is above the baseline you see at comparable healthcare payers. That volume reflects active pipeline buildout inside CVS Health's broader data platform consolidation rather than backfill churn alone. Layoff risk over the next 30 days is low, and there are no tracked layoffs in the window to flag. The direction of travel looks like continued investment in cloud migration and data platform standardization over the next 12 months, with the Hadoop-to-cloud transition still generating a steady workload. Someone joining now is more likely to ride a moderate expansion than to absorb a reduction, though enterprise healthcare organizations can shift hiring posture quickly when membership or regulatory conditions change.
Aetna data engineering tech stack
The languages, storage, and processing tools Aetna data engineers actually work with, grouped by what they do. Tailor your system-design answers to this stack.
Aetna sits inside CVS Health, which means data engineering here is shaped by one of the most data-dense sectors you can work in: claims adjudication, member eligibility, pharmacy benefit management, and clinical risk scoring all generate event streams that have to be processed reliably and under HIPAA constraints. The stack centers on Hadoop, GCP and AWS, with Python, Java and SQL doing the heavy lifting across batch pipelines and reporting layers. That Hadoop footprint signals a large, mature data estate where legacy compatibility still drives architectural decisions alongside the cloud migration work on GCP and AWS. Engineers who join now will spend real time maintaining and modernizing pipelines, writing Python transformations, and building the kind of fault-tolerant batch infrastructure that healthcare data SLAs demand. The regulatory surface is not background noise here; it shapes schema design, retention policy, and access control from day one.
SQLAetna data engineer job openings
A live read on what they are hiring: open roles, recent postings, where, and at what level.
Build and optimize real-time data pipelines using Kafka, CDC, and streaming frameworks
Data Engineer to analyze data engineering problems and develop, build and manage large-scale data structures, pipelines and efficient Extract/Load/Transform (ETL) workflows to address complex problems and support business applications.
Contributing to large-scale applications development, data science, or data analytics projects
Creation of SQL queries and procedures to extract data based on business requirements
Data Engineer to analyze data engineering problems and develop, build, and manage large-scale data structures, pipelines, and efficient Extract/Load/Transform (ETL) workflows to address complex problems and support business applications.
Position Summary: Aetna Resources, LLC, a CVS Health company, is hiring for the following role in Hartford, CT: Data Engineer to develop, build, and manage large-scale data structures, pipelines, and efficient Extract/Load/Transform (ETL) workflows to address complex problems and support business applications.
Position Summary: Aetna Resources LLC, a CVS Health company, is hiring for the following role in Irving, TX: Data Engineer to develop, build and manage large-scale data structures, pipelines and efficient Extract/Load/Transform (ETL) workflows to address complex problems and support business applications.
Data Engineer to Design, build, and manage large-scale data pipelines and backend services to support analytics, machine learning and AI platform initiatives.
Data Engineer to design, build and manage large scale data structures, pipelines and efficient Extract/LoadfTransform (ETL) workflows to support business applications.
Data structures and pipelines to organize, collect and standardize data to generate insights and addresses reporting needs; write ETL (Extract/Transform/Load) processes, design database
Position Summary: Aetna Resources LLC, a CVS Health company, is hiring for the following role in Blue Bell, PA: Staff Data Engineer to Develop, build and manage large-scale data structures, pipelines and efficient Extract/Load/Transform (ETL) workflows to address complex problems and support business applications.
Position Summary: Caremark LLC., a CVS Health company, is hiring for the following role in Alpharetta, GA: Staff Data Engineer to develop, build, and manage large-scale data structures, pipelines, and efficient Extract/Load/Transform (ETL) workflows to address complex problems and support business applications.
Position Summary: Caremark LLC, a CVS Health company, is hiring for the following role in Irving, TX: Staff Data Engineer to design, build and manage large scale data structures, pipelines and efficient Extract/Load/Transform (ETL) workflows to support business applications.
Position Summary: Caremark LLC, a CVS Health company, is hiring for the following role in Irving, TX: Staff Data Engineer to develop, build and manage large-scale data structures, pipelines and efficient Extract/Load/Transform (ETL) workflows to address complex problems and support business applications.
Practice for the Aetna loop
Round by round, the problems our model predicts for this company's interview. Rehearse the shapes their panels keep returning to.
Seniority targeting skews toward the middle and top of the ladder: 14 mid-level and 19 staff reports in a pool of 45 means Aetna is hiring people who can operate with limited hand-holding and own full pipeline domains. If you're a mid-level engineer with 4 to 6 years of experience in healthcare data, claims processing, or regulated industries, this is worth pursuing seriously. Engineers who thrive here tend to be patient with large legacy systems, comfortable in Java and Python in the same repo, and interested in data problems that have genuine downstream impact on care decisions. If you need a fast-moving product environment or a modern lakehouse stack from the start, you'll likely find the pace and tooling frustrating. For a convinced candidate, the loop focuses on pipeline architecture, so prep your pipeline design reasoning and be ready for the screen to go deep on Python before you reach architecture discussions.
Preparing for the Aetna loop
The round-by-round process, example questions, and prep plan are on the interview guide.
Compare Aetna with other data engineering employers
How the role, pay, and loop stack up against peer companies.
Prepare at Aetna interview difficulty
- 01
Reading a solution is not the same as writing one
Every engineer who has frozen on a query they had read a dozen times knows the gap. The only preparation that closes it is producing the answer yourself, under time, before the interview does it for you
- 02
76% of hiring managers reject on the coding task, not the resume
From HackerRank's 2024 Developer Skills Report. Candidates who look strong on paper still fail the live screen if they haven't done timed, executable practice
- 03
5 problem shapes cover 80% of data engineer loops
Dedup, sessionization, top-N-per-group, slowly-changing dimensions, partition tricks. Writing the shapes by hand turns the unfamiliar into pattern recognition