• ℹ️ Instructions for Filling Out the Scorecard Table

Skills evaluated during the technical interview

• Prioritization: Not in the “About you” section since it can’t be quantified by looking at past experiences. Data is a role where everyone comes to you asking for new information. It’s important to ask “why”
  • Questions to ask:
    • “CFO comes with a data ask [details at the end of the page] to you, how do you react.”,
  • Indicators: say no often (how often), one time you solved an ask in a resource-efficient way,
  • What excellent looks like: do a first assessment, this we can do easily, it’s not excalty what you want but it’s quick. We can do exactly as you want 10x. They should be challenging. I have no idea of how complicated. They come back
• Managed people in the past:
  • Questions to ask: What’s your management take? Max team size? (tricky question, must not be proud of team size but of achievements)
  • What excellent looks like: has managed data engineers and data analysts successfully, proud of their growth, proud their are independant
• Communication with other teams:
  • Questions:
    • Tell us a time where you worked on a project involving 2-3 different teams at a company?
  • What great looks like: no politics, straight to people, didn’t create conflict, peaceful resolution
• Evangelization:
  • how do you educate team members outside of data team how to query data and know what’s there?
  • What great looks like: data leaders in each teams, workshops, office hours, great documentation
• Product analytics on mobile:
  • Have you used client-side analytics tools before? On mobile specifically?
  • What great looks like: used mobile tools, knows why Amplitude is better vs Google Analytics
• Product analytics
  • Questions: have you ran A/B tests for product before? What are the pitfalls to avoid?
  • What great looks like: talk about retention, cohort, reactivation, funnels. Has really run A/B tests: don’t believe too good to be true, double check implementation, cross-check data
• Finance:
  • Questions:
    • Tell us about where did the data consumed by the board / execs came from?
    • Did you work with subscriptions revenue before? Can MRR be above Month revenue? Can it be below?
• Self-serve (don’t mention self-serve, must come naturally)
  • Questions: In your opinion, if someone outside the data team has a question. What’s the process for them to get the answer?
  • What great looks like: self-serve
• Delivering insights: key decisions that lead to company changing
  • Questions: did it happen that you’ve uncovered something in the data that lead to the company changing trajectory?

Skills evaluated during the technical test

• Hands-on: can code
  • Infra as code
  • DBT, SQL
  • Python: linter etc