Data Engineering at Epic

Roles, Comp & Culture

An L3 entry data engineer at Epic sits around $90K total comp from 12 verified salary datapoints. Epic pays data engineers below other Technology companies. Reviews put them at 3.3 on Glassdoor, toward the bottom of the pack. Employee sentiment at Epic reads neutral and employee happiness is trending up over the past year. Layoff risk scores low for the next 30 days.

Last updated: Proudly published by: Jeff Wahl

Epic data engineer compensation

Each level's figure is the median of individual Epic 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.

L3Entry$90Kmedian
Base$88KRange$86K–$108KReports12 · 0-2 yrsEpic loop
Updated 12 verified salary reports

Epic 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.

Neutraltrending up over the past year
20252026
Updated Epic employee happiness

Preparing for the Epic loop

The round-by-round process, example questions, and prep plan are on the interview guide.

Compare Epic with other data engineering employers

How the role, pay, and loop stack up against peer companies.

02 / Why practice

Prepare at Epic interview difficulty

  1. 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

  2. 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

  3. 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

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