What level is Senior Data Engineer at Microsoft?

Microsoft uses 63-64 to designate Senior Data Engineers; this is an IC-track level focused on independent technical leadership and cross-team influence.

How much does a Microsoft Senior Data Engineer make?

Microsoft Senior Data Engineer offers span $146K-$219K across 12 samples from 2026, with a median of $207K, median base $154K and median annual equity $32K. Typical experience range: 5-9 years..

How is the Senior Data Engineer loop different from other levels at Microsoft?

Senior Data Engineer loops run the same stages as other levels, but interviewers calibrate difficulty to independent technical leadership and cross-team influence, especially around independent system design and cross-team influence.

How long should I prepare for the Microsoft Senior Data Engineer interview?

8-10 weeks is the standard window for a working DE. Less than 4 weeks almost always means cutting the behavioral prep short.

Does Microsoft interview data engineers differently than software engineers?

The tracks diverge. DE at Microsoft weights SQL and pipeline-design rounds, and interviewers expect specific production data experience that SWE loops don't probe.

Interview Guide

Microsoft Senior Data Engineer Interview (63-64)

Hiring for Senior Data Engineer at Microsoft (63-64) runs Azure-focused with a strong growth-mindset framing in behavioral rounds. The hiring bar is independent technical leadership and cross-team influence; the median candidate brings 5-8 years of DE experience.

Compensation

$170K–$215K base • $290K–$400K total (63-64)

Loop duration

4 hours onsite

Rounds

5 rounds

Location

Redmond, Bay Area, NYC, Atlanta, Dublin, Hyderabad

Compensation

Microsoft Senior Data Engineer total comp

Across 12 samples

Offer-report aggregate, 2026. Level mapped: L5. Typical experience: 5-9 years (median 7).

25th percentile

$146K

Median total comp

$207K

75th percentile

$219K

Median base salary

$154K

Median annual equity

$32K

Tech stack

What Microsoft senior data engineers actually use

Across 5 open roles

Tools and languages mentioned most often in Microsoft's currently-active data engineer postings. Each chip links to an interview prep page for that tool.

Azure5AWS3Databricks2Fabric2GCP2PostgreSQL2Hadoop2Synapse2Terraform1CI/CD1Spark1 Airflow1

Prepare for the interview

01 / Open invite

02min.

Walk into Microsoft knowing the Python pattern they'll test.

a Microsoft Python query, the same shape a screen would give you.

The diff against expected. Where ties broke. What you missed.

sandbox

1def sessionize(events):

2 sessions = []

3 for e in events:

4 if gap_minutes(e) > 30:

Execute your solution0.4s avg.

MicrosoftInterview question

Solve a Microsoft problem

Round focus

Domain concentration by round

Across 5 job descriptions

What each Microsoft round typically tests, weighted across 5 live senior data engineer postings. The bars show the relative emphasis of each domain.

Online Assessment

Python89%

SQL40%

Architecture10%

Spark8%

Modeling5%

Phone Screen

Python68%

SQL63%

Architecture39%

Spark16%

Modeling8%

Onsite Loop

Architecture65%

Modeling30%

SQL28%

Python28%

Spark13%

Practice problems

Microsoft senior data engineer practice set

4 problems

Practice sets surfaced for Microsoft senior data engineer candidates by the same model that reads their job postings. Each card opens a working coding environment.

SQLmedium~10 min

Subscribers Without Premium

Pull basic-plan subscribers who never upgraded to premium from the subscriptions data. The retention team wants to run a winback campaign targeting this group.

Open in practice environment→

Pythonhard~5 min

The Overlap

Your monitoring system logs server maintenance as `[start, end]` minute ranges, and windows that overlap or sit back-to-back really describe one continuous outage. Collapse the `windows` so any that overlap or touch at an endpoint become a single range, and return them ordered by start time. Two windows touch when one ends exactly where the next begins.

Open in practice environment→

SQLeasy~10 min

Nth Largest Value

The compensation team needs the second-highest unique metric value in the performance table as a benchmark for setting the next salary band. Return that single value, or NULL if the data does not have enough unique values.

Open in practice environment→

Pythoneasy~10 min

Progress Milestones

Given a positive integer k, return a list of 10 milestone values at 10%, 20%, ..., 100% of k. Each value is int(k * pct / 100). Return the list of 10 integers in order.

Open in practice environment→

Daily signup-to-purchase funnel

Count signups and first-time purchases per day. Product-company favorite.

	WITH first_purchase AS (
	SELECT
	user_id,
	MIN(event_date) AS first_purchase_date
	FROM events
	WHERE event_type = 'purchase'
	GROUP BY user_id
	)

	SELECT
	e.event_date AS day,
	COUNT(*) FILTER (
	WHERE e.event_type = 'signup'
	) AS signups,
	COUNT(*) FILTER (
	WHERE e.event_type = 'purchase'
	AND e.event_date = fp.first_purchase_date
	) AS first_purchases
	FROM events AS e
	LEFT JOIN first_purchase AS fp
	ON e.user_id = fp.user_id
	GROUP BY e.event_date
	ORDER BY e.event_date

Prepare for the interview

03 / From the bank03 of many

03hand-picked.

The Vowel Hunt

Easy10 min

Just the vowels. All of them.

Open the sandbox

Pick your level

MicrosoftL3Points of Order MicrosoftL4Quantile Calculator AppleL5The Chain Transform

Pulled from debriefs where Python parsing was the gate.

The loop

How the interview actually runs

01Recruiter screen

30 min

Standard call, background, motivations, level calibration. Microsoft is friendlier than FAANG peers in screen tone.

→Mention Azure/Synapse/Fabric experience if you have it
→Be specific about the product area interest: Azure Data, Power BI, Dynamics, Xbox, Office
→Ask about growth trajectory. Microsoft has strong internal mobility

02Technical screen

60 min

SQL + coding. Microsoft loves T-SQL syntax specifically. Problems involve stored procedures, CTEs, window functions, and data validation logic.

→Know T-SQL specifics: MERGE, APPLY, CROSS APPLY, OUTPUT clause
→Expect problems on event stores, telemetry, or Azure service usage
→Show familiarity with Azure Data Factory / Synapse if the team uses them

03Onsite: Data system design

60 min

Design a data pipeline or analytics system, usually with Azure services as the default stack. Microsoft interviewers are pragmatic and expect cost awareness.

→Default to Azure services: ADF for orchestration, Synapse for warehouse, ADLS for lake
→Cost questions land. Microsoft cares about Azure consumption
→Cover failure modes and retry/backoff explicitly

04System design (pipeline architecture)

60 min

Design a production pipeline end-to-end: ingestion, transformation, storage, consumers, SLAs, failure modes, backfill strategy, and cost trade-offs. At senior level, you drive the conversation without prompting. Expect follow-ups about scale, cross-team coordination, and operational load.

→Anchor on the SLA and data shape before diagramming
→Discuss idempotency, partitioning, and backfill explicitly
→Estimate cost: 'This pipeline will cost roughly $X/month at this volume'

05Growth mindset / as-appropriate

60 min

Behavioral round heavily themed around growth mindset: learning from failure, seeking feedback, adapting. Microsoft interviewers are trained on this framework explicitly.

→Have 2+ stories about changing your mind based on new information
→Growth-mindset language: 'I learned that I had been assuming X'
→Feedback stories: what critical feedback did you get, how did you act on it

Level bar

What Microsoft expects at Senior Data Engineer

Independent technical leadership

Senior DEs drive pipeline designs without engineering manager involvement. Interviewers probe whether you can decompose ambiguous requirements, make architecture trade-offs, and defend your choices under scrutiny.

Cross-team coordination

Senior scope regularly spans multiple teams. Expect scenarios about a downstream team missing an SLA because of a change you made, or negotiating a schema migration with the team that owns the upstream source.

Production operational rigor

Fluent in on-call, alerting, data quality checks, and incident response. Dive-deep stories at this level should include correlating a metric drop to a specific commit or a timezone bug or a subtle ordering issue, not 'I looked at the logs.'

Microsoft-specific emphasis

Microsoft's loop is characterized by: Azure-focused with a strong growth-mindset framing in behavioral rounds. Calibrate your preparation to that, generic FAANG prep will not close the gap on company-specific expectations.

Behavioral

How Microsoft frames behavioral rounds

Growth mindset

Satya Nadella's cultural north star. Microsoft interviewers explicitly score on this dimension.

“Tell me about a time you failed at something significant and what you did next.”

Customer obsession

Microsoft has shifted toward customer-facing thinking even for backend roles. DEs should think about the analyst or developer consuming their data.

“How have you made a downstream user's job easier through your data work?”

Respectful disagreement

Microsoft's culture rewards strong opinions delivered with humility. Aggressive-genius stories land poorly.

“Describe a technical disagreement and how you handled it.”

Cross-organization collaboration

Microsoft is federated. Azure, Office, Xbox, Dynamics all have different cultures. Working across them requires diplomacy.

“Tell me about collaborating with a partner team that had different goals.”

Prep timeline

Week-by-week preparation plan

8-10 weeks out

Foundations and gap analysis

·Do 10 medium SQL problems. Note which patterns feel slow
·Write out 2-3 behavioral stories per value, Microsoft weights this round heavily
·Read Microsoft's public engineering blog for recent architecture patterns
·Review your prior production work, pick 3-5 projects you can discuss in depth

6 weeks out

SQL and coding fluency

·Practice window functions until DENSE_RANK, ROW_NUMBER, LAG, LEAD are reflex
·Do 20+ Microsoft-style problems in their domain
·Time yourself: 25 min per medium, 35 min per hard
·Record yourself narrating approach aloud, communication is graded

4 weeks out

Pipeline system design

·Design 5 pipelines on paper: daily aggregation, clickstream, CDC, ML feature store, real-time alerting
·For each, write SLA, partition strategy, backfill plan, and cost estimate
·Practice with a friend, senior-level system design is 50% driving the conversation
·Review Microsoft's open-source and engineering blog for in-house patterns

2 weeks out

Behavioral polish and mock loops

·Rehearse every story out loud. Cut to 2-3 minutes each
·Run 2 full mock loops with a senior DE or coach
·Identify your 3 weakest behavioral areas and draft additional stories
·Review recent Microsoft news or earnings call for fresh talking points

Week of

Taper and logistics

·No new content. Review your notes only
·Sleep. Mental energy matters more than one more practice problem
·Confirm logistics: laptop charged, shared-doc tool tested, snack and water nearby
·Remember: the loop is rooting for you to raise the bar, not to fail

Other guides you'll want

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FAQ

Common questions

What level is Senior Data Engineer at Microsoft?: Microsoft uses 63-64 to designate Senior Data Engineers; this is an IC-track level focused on independent technical leadership and cross-team influence.
How much does a Microsoft Senior Data Engineer make?: Microsoft Senior Data Engineer offers span $146K-$219K across 12 samples from 2026, with a median of $207K, median base $154K and median annual equity $32K. Typical experience range: 5-9 years..
How is the Senior Data Engineer loop different from other levels at Microsoft?: Senior Data Engineer loops run the same stages as other levels, but interviewers calibrate difficulty to independent technical leadership and cross-team influence, especially around independent system design and cross-team influence.
How long should I prepare for the Microsoft Senior Data Engineer interview?: 8-10 weeks is the standard window for a working DE. Less than 4 weeks almost always means cutting the behavioral prep short.
Does Microsoft interview data engineers differently than software engineers?: The tracks diverge. DE at Microsoft weights SQL and pipeline-design rounds, and interviewers expect specific production data experience that SWE loops don't probe.

Interview Prep

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