Interview Guide

Pinterest Junior Data Engineer Interview (L3)

Hiring for Junior Data Engineer at Pinterest (L3) runs Visual-discovery platform with inspiration-driven engineering and careful, thoughtful culture. The hiring bar is foundational SQL fluency and a willingness to learn production systems; the median candidate brings 0-2 years of DE experience.

Compensation

$130K–$160K base • $165K–$225K total

Loop duration

3 hours onsite

Rounds

4 rounds

Location

San Francisco, Seattle, NYC, Toronto, Dublin

Tech stack

What Pinterest junior data engineers actually use

Across 2 open roles

These are the tools that show up in Pinterest's DE job descriptions right now. Click any chip to drop into an interview prep page for it.

Round focus

Domain concentration by round

Across 2 job descriptions

Where each domain tends to come up in Pinterest's loop, derived from 2 current junior data engineer job descriptions. Longer bars mean heavier weight.

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

04Onsite: 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 Junior Data Engineer

SQL foundations

Junior rounds weight SQL the heaviest. Expect multi-table joins, aggregations, window functions, and one harder query involving self-joins or recursive CTEs. You do not need to design systems at this level, but you do need SQL to be reflexive.

Learning orientation

Interviewers probe how you pick up new tools. A strong story about learning a new stack in a prior role (even an internship or side project) can outweigh gaps in production experience.

Basic pipeline awareness

You should know what ETL vs ELT means, what a data warehouse is, and why idempotency matters, even if you have not built a production pipeline yourself.

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 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
  • ·Shore up data engineering foundations: SQL, Python, one warehouse (Snowflake/BigQuery/Redshift)
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

Pipeline awareness and behavioral depth

  • ·Review pipeline architecture basics: idempotency, partitioning, backfill
  • ·Practice explaining a pipeline you've worked on end-to-end in 5 minutes
  • ·Refine behavioral stories based on mock feedback
  • ·Do 10 more SQL problems at medium difficulty
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 mid-level 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: interviewers want to find reasons to hire you, not to reject you

FAQ

Common questions

What level is Junior Data Engineer at Pinterest?
At Pinterest, Junior Data Engineer corresponds to the L3 level. The bar emphasizes foundational SQL fluency and a willingness to learn production systems without people-management responsibilities.
How much does a Pinterest Junior Data Engineer make?
Total compensation for Pinterest Junior Data Engineer ranges $130K–$160K base • $165K–$225K total. Ranges shift by team and negotiation.
How is the Junior Data Engineer loop different from other levels at Pinterest?
The format of the loop matches other levels; difficulty and evaluation shift to foundational SQL fluency and a willingness to learn production systems, and questions at this level dig into SQL fundamentals, learning orientation, and basic pipeline awareness.
How long should I prepare for the Pinterest Junior Data Engineer interview?
Most working DEs find 6-8 weeks is about right. The technical prep scales with experience; the behavioral story bank is where candidates underestimate time.
Does Pinterest interview data engineers differently than software engineers?
Yes, the DE track at Pinterest emphasizes SQL depth, warehouse and pipeline design, and real production data experience (late data, backfills, quality checks), which generalist SWE loops don't test.