Data Engineering at Cardinal Health
Roles, Comp & Culture
An L6 staff data engineer at Cardinal Health sits around $144K total comp from 10 salary datapoints. The ladder runs from about $144K at senior up to $144K. Cardinal Health pays data engineers slightly below other Healthcare companies. Reviews put them at 3.6 on Glassdoor, a little below the middle of the pack. Employee sentiment at Cardinal Health reads neutral and employee happiness has held flat over the past year. Layoff risk scores low for the next 30 days.
Cardinal Health data engineer compensation
Each level's figure is the median of individual Cardinal Health 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.
Cardinal Health 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.
Recent Cardinal Health events
Layoffs, leadership changes, and other major moves at the company, with dates.
- Exec departureMar 2026Leadership change
- Exec departureMar 2026Leadership change
- Exec departureMar 2025Leadership change
Notable company events we track, with dates.
Preparing for the Cardinal Health loop
The round-by-round process, example questions, and prep plan are on the interview guide.
Compare Cardinal Health with other data engineering employers
How the role, pay, and loop stack up against peer companies.
Prepare at Cardinal Health 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