Data Engineering at University of California, San Francisco
Roles, Comp & Culture
An L4 mid data engineer at University of California, San Francisco sits around $130K total comp from 13 verified salary datapoints. The ladder runs from about $129K at entry up to $130K. University of California, San Francisco pays data engineers slightly below other Technology companies. Reviews put them at 0.0 on Glassdoor, toward the bottom of the pack. Employee sentiment at University of California, San Francisco reads neutral and employee happiness has held flat over the past year. Layoff risk scores low for the next 30 days. 1 data engineering role is open right now.
University of California, San Francisco data engineer compensation
Each level's figure is the median of individual University of California, San Francisco 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.
University of California, San Francisco 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.
University of California, San Francisco data engineering tech stack
The languages, storage, and processing tools University of California, San Francisco data engineers actually work with, grouped by what they do. Tailor your system-design answers to this stack.
SQLUniversity of California, San Francisco data engineer job openings
A live read on what they are hiring: open roles, recent postings, where, and at what level.
Preparing for the University of California, San Francisco loop
The round-by-round process, example questions, and prep plan are on the interview guide.
Compare University of California, San Francisco with other data engineering employers
How the role, pay, and loop stack up against peer companies.
Prepare at University of California, San Francisco 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