Interview Guide

Pinterest Principal Data Engineer Interview (L7)

Pinterest (L7) Principal Data Engineer loop: Visual-discovery platform with inspiration-driven engineering and careful, thoughtful culture. Bar at this level: industry-level technical credibility and company-wide strategic impact. Typical 12+ years of data engineering experience.

Compensation

$285K–$365K base • $610K–$860K total

Loop duration

4 hours onsite

Rounds

5 rounds

Location

San Francisco, Seattle, NYC, Toronto, Dublin

Tech stack

What Pinterest principal data engineers actually use

Across 2 open roles

What Pinterest currently advertises as required for data engineer roles. Chips link into tool-specific interview guides.

Round focus

Domain concentration by round

Across 2 job descriptions

Per-round concentration of each domain in Pinterest's interview, derived from the skills emphasized across 2 current principal data engineer postings. Higher bars mean more questions of that type in that round.

Online Assessment

Python88%
SQL43%
Architecture12%
Spark9%
Modeling6%

Phone Screen

SQL70%
Python68%
Architecture25%
Spark14%
Modeling9%

Onsite Loop

Architecture63%
Modeling33%
SQL32%
Python32%
Spark14%
Prepare for the interview
01 / Open invite
02min.

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

a Pinterest 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:
5
Execute your solution0.4s avg.
PinterestInterview question
Solve a Pinterest problem

Rolling 7-day active users

Count distinct users active in the trailing 7 days for each date. Product analytics staple.

1WITH dates AS (
2 SELECT DISTINCT
3 activity_date
4 FROM activity
5)
6
7SELECT
8 d.activity_date AS day,
9 COUNT(DISTINCT a.user_id) AS rolling_7d_users
10FROM dates AS d
11INNER JOIN activity AS a
12 ON a.activity_date <= d.activity_date
13 AND JULIANDAY(d.activity_date) - JULIANDAY(
14 a.activity_date
15 ) < 7
16GROUP BY d.activity_date
17ORDER BY d.activity_date
Prepare for the interview
03 / From the bank03 of many
03hand-picked.

The Balanced Sum

Easy10 min

Some numbers have a rare quality that mathematicians revere.

Pulled from debriefs where Python parsing was the gate.

The loop

How the interview actually runs

01Recruiter screen

30 min

Pinterest's product is visual inspiration. DE work splits across Ads, Home Feed ranking, Creator, Shopping, and Trust & Safety.

  • Know Pinterest's product vocabulary: Pin, Board, Save, Repin, Close-up
  • Recommendation-system experience helps for Feed roles
  • Pinterest's scale is smaller than Meta but similar shape

02Technical phone screen

60 min

SQL with engagement data: session analysis, Pin-save rates, board-completion metrics.

  • Funnel SQL: impression → click → save → buy
  • Cohort retention is a recurring theme
  • Pinterest uses AWS + Presto + Druid heavily

03Onsite: data architecture

60 min

Design a pipeline for Pinterest: Home Feed ranking features, Ads attribution, shopping catalog integration, Trust & Safety flagging.

  • Feature-store design for recommendation is central
  • Real-time vs batch tradeoffs matter
  • Druid is Pinterest's OLAP of choice; familiarity is a plus

04Exec conversation / technical vision

60 min

Usually with a director, VP, or distinguished engineer. Less whiteboarding, more conversation about technical vision: 'Where should our data platform be in 3 years?' 'How would you make the case to the CEO for a $10M data investment?' Evaluators look for business alignment, long-term thinking, and executive presence.

  • Prepare 2-3 industry-level opinions with clear reasoning
  • Translate technology into business impact: revenue, cost, risk, velocity
  • Ask sharp questions about the company's data strategy and current pain points

05Onsite: behavioral

45 min

Pinterest's culture emphasizes thoughtfulness, inclusion, and creator empathy. Stories about polish and user impact land well.

  • Creator empathy distinguishes Pinterest from pure ad platforms
  • Slow, considered work is valued over blitz-shipping
  • Inclusion is a genuine cultural pillar

Level bar

What Pinterest expects at Principal Data Engineer

Company-wide impact

Principal DEs operate at the level of 'this changed how engineering gets done at the company.' Interviewers expect one or two career-defining projects with measurable multi-team or company-level outcomes.

Industry credibility

OSS contributions, conference talks, published articles, or patents. Not required but heavily weighted. The bar is 'the industry knows your name in this niche.'

Executive communication

Ability to explain technical tradeoffs to a non-technical CEO in 5 minutes. Interviewers roleplay execs and test whether you can resist jargon and anchor on business value.

Strategic foresight

Evidence of technology bets you made 2-3 years out that paid off (or didn't, with honest retrospective). Principal is a role about being right about the future, not just the present.

Pinterest-specific emphasis

Pinterest's loop is characterized by: Visual-discovery platform with inspiration-driven engineering and careful, thoughtful culture. Calibrate your preparation to that, generic FAANG prep will not close the gap on company-specific expectations.

Behavioral

How Pinterest frames behavioral rounds

Put Pinners first

Pinterest's user-obsession framing. Engineers who frame work in user-impact terms resonate.

How has a Pinner (user) observation changed your work?

Aim for extraordinary

Pinterest rewards craft and polish. Half-done work stands out negatively.

What's a piece of engineering polish you insisted on?

Create belonging

Pinterest's inclusion commitment is real. Hiring panels evaluate this genuinely.

How have you made a team more inclusive?

Own it

Pinterest engineers are expected to drive work end-to-end with judgment.

Describe an initiative you drove without explicit authority.

Prep timeline

Week-by-week preparation plan

8-10 weeks out
01

Foundations and gap analysis

  • ·Do 10 medium SQL problems. Note which patterns feel slow
  • ·Write out 2-3 behavioral stories per value, Pinterest weights this round heavily
  • ·Read Pinterest'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
02

SQL and coding fluency

  • ·Practice window functions until DENSE_RANK, ROW_NUMBER, LAG, LEAD are reflex
  • ·Do 20+ Pinterest-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
03

Platform-level system design

  • ·Design 3-5 multi-system platforms: metadata store, shared ingestion, governance layer
  • ·Prepare 2-3 stories where you drove technical direction across teams
  • ·Practice mock interviews with another staff+ engineer
  • ·Review Pinterest's publicly described platform work for recent architectural shifts
2 weeks out
04

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 Pinterest news or earnings call for fresh talking points
Week of
05

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

FAQ

Common questions

What level is Principal Data Engineer at Pinterest?
Principal Data Engineer maps to L7 on Pinterest's engineering ladder. This is an individual contributor level; expectations focus on industry-level technical credibility and company-wide strategic impact.
How much does a Pinterest Principal Data Engineer make?
Total compensation for Pinterest Principal Data Engineer ranges $285K–$365K base • $610K–$860K total. Ranges shift by team and negotiation.
How is the Principal Data Engineer loop different from other levels at Pinterest?
The rounds look similar, but the bar calibrates to seniority. Principal Data Engineer is evaluated on industry-level technical credibility and company-wide strategic impact. Questions at this level probe industry-level credibility and company-wide impact.
How long should I prepare for the Pinterest Principal Data Engineer interview?
Plan for 12+ weeks of prep if you're already a working DE. Under 4 weeks rushes the behavioral prep, which takes the most time.
Does Pinterest interview data engineers differently than software engineers?
They differ meaningfully. Pinterest's DE loop has heavier SQL, replaces the general system-design with a data-specific one (pipelines, warehouse design), and expects production data ops experience.