Data Engineering at MathWorks
Roles, Comp & Culture
An L4 mid data engineer at MathWorks sits around $165K total comp from 20 verified salary datapoints. The ladder runs from about $156K at entry up to $165K. MathWorks pays data engineers in line with other Technology companies. Reviews put them at 4.3 on Glassdoor, among the highest of any company here. MathWorks employees report healthy morale and employee happiness is trending up over the past year. Layoff risk scores low for the next 30 days. 1 data engineering role is open right now.
MathWorks data engineer compensation
Each level's figure is the median of individual MathWorks 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.
MathWorks 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.
MathWorks data engineer job openings
A live read on what they are hiring: open roles, recent postings, where, and at what level.
Preparing for the MathWorks loop
The round-by-round process, example questions, and prep plan are on the interview guide.
Compare MathWorks with other data engineering employers
How the role, pay, and loop stack up against peer companies.
Prepare at MathWorks 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