Amgen Data Engineer Interview Guide

The Amgen data engineer loop, round by round: what each stage tests, example questions with the guidance interviewers actually score, the mistakes that sink strong candidates, and how to prepare.

Last updated: August 2, 2026Proudly published by: Jeff Wahl

What the Amgen loop tests: domains and difficulty

Our prediction of the question mix by domain and difficulty for this company's data engineer loop, from live listings and interview reports.

By domain

SQL

57%

Python

43%

By difficulty

Easy

50%

Medium

29%

Hard

21%

The domain and difficulty mix we predict for a Amgen data engineer loop, across 14 problems. It updates as more Amgen data lands.

Updated Aug 2, 202614 predicted Amgen problems

2 real Amgen interview questions

Reported by candidates from real loops, tagged by domain, round, level, and year. Expand for what the round is scoring.

SQLL5 · 2024

Different between union and union all.

Phone screen · screen sql

SQLL5 · 2024

Different between union and union all.

Behavioral

Where offers are lost

Offers get lost when candidates treat Amgen like a pure-tech shop. Engineers who come in optimizing for elegant abstractions or minimal-overhead pipelines, without acknowledging the regulatory surface, read as a poor fit regardless of technical ability. The failure mode in the architecture rounds is proposing a design that would work well in a startup context but glosses over lineage, idempotency, or schema versioning in an environment where those aren't optional. The inverse behavior that reads as a hire is naming the constraint unprompted: if a candidate explains that a particular design choice preserves auditability or simplifies a potential audit trail, that lands differently here than it would at a product company. With 40 salary reports and a small active headcount signal, the team is deliberate about who they bring in, which makes cultural fit with the regulated-domain mindset a real filter.

Try a Amgen-style SQL round

Find every user active on 3 or more CONSECUTIVE days. This gaps-and-islands shape shows up in nearly every DE SQL round. Edit the query and run it against the seed data.

	/* Users active on 3+ consecutive days. */
	/* Hint: date minus a per-user ROW_NUMBER is constant within a streak. */
	WITH streaks AS (
	SELECT
	user_id,
	activity_date,
	activity_date - CAST(
	(ROW_NUMBER() OVER (
	PARTITION BY user_id
	ORDER BY activity_date
	))
	AS INT
	) AS grp
	FROM user_sessions
	)

	SELECT
	user_id
	FROM streaks
	GROUP BY user_id, grp
	HAVING COUNT(*) >= 3

Practice the Amgen loop

The problems our model expects in this company's interview, grouped by round. Work the shapes that come up, not the ones that read well on a list.

What the loop filters for

Amgen's loop is designed to surface engineers who can operate responsibly inside a regulated data environment, not just engineers who can build fast. The clinical and commercial data that moves through Amgen's pipelines touches FDA-adjacent domains, which means the company needs people who internalize auditability as a design requirement, not an afterthought. What the process filters for is disciplined judgment: can you make schema decisions that hold up under compliance review, document lineage without being asked, and flag a data quality issue before it propagates into a downstream report that someone stakes a regulatory submission on? Generic pipeline competence is assumed. The signal the loop is extracting is whether your instincts have been calibrated by environments where correctness carries consequences beyond a broken dashboard.

SQL3 to work

High Volume Batch Jobs

Python3 to work

Frequency CountingSolve →

All Amgen-style problems →

Amgen compensation and culture

The numbers, tech stack, and team structure live on the company overview.

Data engineering at Amgen→

The role, comp by level, tech stack, teams, and culture signals.

Compare Amgen with other data engineering employers

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

Data engineering at Airbnb→

Compare the role, comp, and interview loop.

Data engineering at Amazon→

Compare the role, comp, and interview loop.

Data engineering at Apple→

Compare the role, comp, and interview loop.

Data engineering at Databricks→

Compare the role, comp, and interview loop.

02 / Why practice

Prepare at Amgen 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

Practice Amgen-level SQL

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