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Whether what you did before predicts what you will do here: the problem you owned, the decision you drove, the friction you handled, and the number that moved. It is scored against a rubric, not on charm — Google’s published guide to structured interviewing grades each answer poor, borderline, solid or outstanding against examples written before the interview, with follow-ups fixed in advance. Amazon scores its Leadership Principles in every round and adds a Bar Raiser from outside the team, who shares the final hiring decision with the hiring manager. Meta runs a standalone behavioral round, and Netflix and Airbnb hire against written values. Services firms and Indian product companies end the loop on a managerial or HR round built from the same prompts.
Nobody walks into a loop with forty rehearsed answers. Write these 9 stories down once, in the five parts below, then say each one out loud until it lands in about two minutes. Every slot names the reported questions it answers, and between them they answer the whole Behavioral bank.
01 · Situation
The system, its scale and what was at stake. About a fifth of the time.
02 · Task
What was yours to do, and who was waiting on it. One sentence.
03 · Action
The root cause you found, what you changed, and the trade-off you took. Most of the time goes here.
04 · Result
A before and an after: rows, runtime, cost, SLA, or how many people were affected.
05 · Lesson
What you do differently now, and the check or habit that proves it.
STORY 01
Every data engineering loop asks for one, under a dozen names. It is the story that proves you own what you ship.
STORY 02
Data engineers are trusted on correctness. This is the Dive Deep story, and the one you retell for non-engineers.
STORY 03
Asked in some form in nearly every loop. It is scored on ownership without excuses, and on proof that you changed.
STORY 04
Often the first story in the loop, and the base for the deep dive that follows. Choose the one you know inside out.
STORY 05
Invent and Simplify and Frugality in one story — and cost is a question every data team is asked now.
STORY 06
Stacks change every few years. This story proves you can learn against a deadline and act before everything is known.
STORY 07
The Disagree and Commit story. One good one answers the manager, colleague, team and cross-team versions of the question.
STORY 08
Deliver Results under pressure: what you cut, what you protected, and who heard about it before the date.
STORY 09
The request said one thing and the need was another. This is Customer Obsession for the people who consume data.
Amazon scores these in every round of the loop, not only the behavioral one. Each row gives the principle in Amazon’s words, what it looks like in data work, the reported questions that probe it, and the story to reach for. The marked rows are the ones data engineering candidates report being pressed on hardest.
| Principle | In data work | Asked as | Story |
|---|---|---|---|
| Customer ObsessionMost asked“Leaders start with the customer and work backwards.” | Your customers are the analysts, finance and product teams reading your tables. Work backwards from the decision a table feeds, not from the schema you would like. | The stakeholder who wanted something else | |
| OwnershipMost asked“Leaders are owners.” | Owning a pipeline after it ships: the pager, the backfill, the deprecation. Fixing the upstream cause even when the upstream belongs to another team. | The incident you ran | |
| Invent and Simplify“Leaders expect and require innovation and invention from their teams and always find ways to simplify.” | Replacing forty hand-written jobs with one framework, or deleting a pipeline nobody reads. Fewer moving parts is fewer pages at 3am. | The thing you made simpler or cheaper | |
| Are Right, A Lot“Leaders are right a lot.” | Choosing a table format, a partition key or a model that is still right a year later, and seeking out the person most likely to prove you wrong first. | The thing you had to learn fast | |
| Learn and Be Curious“Leaders are never done learning and always seek to improve themselves.” | Picking up the engine, the format or the business domain the job needed, fast, and saying plainly what you learned the hard way. | The thing you had to learn fast | |
| Hire and Develop the Best“Leaders raise the performance bar with every hire and promotion.” | Reviewing code so the author learns, writing the runbook the next on-call needs, and bringing a new engineer onto the pager. | — | |
| Insist on the Highest Standards“Leaders have relentlessly high standards — many people may think these standards are unreasonably high.” | Data tests, reconciliation and contracts before anyone asks for them. Refusing to publish a number you cannot reconcile to its source. | The numbers that were wrong | |
| Think Big“Thinking small is a self-fulfilling prophecy.” | Proposing the platform, the contract or the migration that removes a whole class of incident, rather than fixing the next one. | The project you are proudest of | |
| Bias for Action“Speed matters in business.” | Stopping a bad write now and investigating after. Shipping the reversible fix tonight and the proper one next sprint. | The incident you ran | |
| Frugality“Accomplish more with less.” | Cutting compute and storage with retention, partition pruning and right-sized clusters, and delivering with the stack you already have. | The thing you made simpler or cheaper | |
| Earn Trust“Leaders listen attentively, speak candidly, and treat others respectfully.” | Telling stakeholders the numbers were wrong before they find out, and owning your part in the post-mortem. | The mistake that was yours | |
| Dive DeepMost asked“Leaders operate at all levels, stay connected to the details, audit frequently, and are skeptical when metrics and anecdote differ.” | Following a wrong number down to the row, the join or the late partition that caused it, instead of stopping at the dashboard. | The numbers that were wrong | |
| Have Backbone; Disagree and Commit“Leaders are obligated to respectfully challenge decisions when they disagree, even when doing so is uncomfortable or exhausting.” | Pushing back on a design, a deadline or a metric definition with evidence, then committing fully once the call is made. | The disagreement | |
| Deliver ResultsMost asked“Leaders focus on the key inputs for their business and deliver them with the right quality and in a timely fashion.” | Landing the migration, the SLA or the launch on time and correct, and telling people early when it will not land. | The deadline that could not move | |
| Strive to be Earth’s Best Employer“Leaders work every day to create a safer, more productive, higher performing, more diverse, and more just work environment.” | Making on-call survivable: fewer false pages, better runbooks, blameless post-mortems. | — | — |
| Success and Scale Bring Broad Responsibility“We started in a garage, but we’re not there anymore.” | Thinking about what your data enables: PII, retention and erasure, and what happens when people are paid on a metric you compute. | The project you are proudest of |
Principle wording: Amazon — Leadership Principles
This round has no question bank behind it — it is judged on how you tell the story, not on recall.
See all six rounds and the plans, or build something and have it reviewed: a daily orders pipeline or a marketplace model.