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 in Seattle make?

Microsoft Senior Data Engineer in Seattle offers span $193K-$257K across 94 samples from 2020-2026, with a median of $224K, median base $161K and median annual equity $33K. Typical experience range: 4-10 years..

Does Microsoft actually hire data engineers in Seattle?

Yes, Microsoft maintains a Seattle office and hires Senior Data Engineer data engineers there. Team assignment may be office-locked or global; confirm with the recruiter before the loop.

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 · 2026

Microsoft Senior Data Engineer Interview in Seattle (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. The Seattle / Bellevue, WA office has its own hiring cadence; the page below adjusts comp bands accordingly.

Compensation

$156K–$198K base • $267K–$368K total (63-64)

Loop duration

4 hours onsite

Rounds

5 rounds

Location

Seattle / Bellevue, WA

Compensation

Microsoft Senior Data Engineer in Seattle total comp

Across 94 samples

Offer-report aggregate, 2020-2026. Level mapped: L5. Typical experience: 4-10 years (median 7).

25th percentile

$193K

Median total comp

$224K

75th percentile

$257K

Median base salary

$161K

Median annual equity

$33K

Median total comp by year

2021

$190K n=17

2022

$209K n=21

2023

$213K n=7

2024

$215K n=9

2025

$243K n=21

2026

$268K n=18

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.

SQLeasy~5 min

Clean Latency Cast

During a data quality investigation, you found that the latency column in service health records contains some non-numeric strings. Return all records with latency converted to an integer, excluding any rows where the conversion would fail. Return all available fields.

Open in practice environment→

Pythoneasy~10 min

The Runner-Up

Return the second-largest distinct value in the input list of integers. If the list has fewer than two distinct values, return None.

Open in practice environment→

Modelinghard~40 min

Content Engagement Data Model

We run a large social content platform. Creators publish posts (text, images, video). Users engage through views, reactions, comments, and shares. The product team needs a data model to power dashboards for content virality, creator performance, and feed ranking signals. Data visualization is also required. Sketch how a virality chart would query this model.

Open in practice environment→

Architecturemedium~20 min

Real-Time POS Ingestion into Snowflake

Our retail stores run point-of-sale terminals that generate transactions all day. The business intelligence team currently gets a nightly batch of sales data but they want same-day visibility. We also have years of historical sales in our Snowflake warehouse that needs to stay consistent with whatever we build. Design a pipeline to bring POS data into Snowflake in near-real-time.

Open in practice environment→

Try itDaily signup-to-purchase funnel

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

funnel.sql

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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 e
LEFT JOIN first_purchase fp ON e.user_id = fp.user_id
GROUP BY e.event_date
ORDER BY e.event_date;
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 e
LEFT JOIN first_purchase fp ON e.user_id = fp.user_id
GROUP BY e.event_date
ORDER BY e.event_date;

Click Run to execute. Edit the code above to experiment.

Seattle / Bellevue, WA

Microsoft in Seattle

No state income tax. AWS and Azure anchor the DE market, with dense mid-to-senior hiring across Amazon, Microsoft, and their ecosystem.

Compensation in Seattle runs roughly 8% below Microsoft's reference band, matching local cost-of-living and market rates. Loop structure in Seattle matches the global Microsoft process; what differs is team placement and the compensation range.

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

Microsoft Senior Data Engineer (global guide)→Microsoft Junior Data Engineer in Seattle→Microsoft Data Engineer in Seattle→Microsoft Staff Data Engineer in Seattle→Microsoft Principal Data Engineer in Seattle→Microsoft Senior Data Engineer in San Francisco Bay Area→Microsoft Senior Data Engineer in New York→Microsoft Senior Data Engineer in Austin→Microsoft Data Engineer Salary→Data Engineer Interview Prep (hub)→

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 in Seattle make?: Microsoft Senior Data Engineer in Seattle offers span $193K-$257K across 94 samples from 2020-2026, with a median of $224K, median base $161K and median annual equity $33K. Typical experience range: 4-10 years..
Does Microsoft actually hire data engineers in Seattle?: Yes, Microsoft maintains a Seattle office and hires Senior Data Engineer data engineers there. Team assignment may be office-locked or global; confirm with the recruiter before the loop.
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.

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Published 2026-04-20Updated 2026-04-20