Team Product Analytics

Backend Engineer

  • Department

    Engineering

  • Location

    Remote (EMEA)

  • Timezone(s)

    GMT +2:00 to GMT -5:00

About PostHog

PostHog helps engineers build better products. We are a single platform to analyze, test, observe, and deploy new features. We give engineers product analytics, session recording, feature flags, A/B testing, event pipelines, SQL access, and a data warehouse… and there’s plenty more to come.

PostHog was created as an open-source project during Y Combinator's W20 cohort and had the most successful B2B software launch on HackerNews since 2012 - with a product that was just 4 weeks old. Since then, more than 35,000 companies have installed the platform. We've had huge success with our paid upgrades, raised $27m from some of the world's top investors, and have shown strong product-led growth - 97% driven by word of mouth. 

Despite the 📉 tech market, we're default alive and doing better than ever!

PostHog makes money from our cloud product, or people can self host the open source project. We average 10% monthly revenue growth and are aiming for $10m ARR in early 2024. While others are focused on layoffs and struggling to grow into huge valuations, we're focusing on an awesome product for end users, hiring a handful of exceptional team members and seeing fantastic increases in revenue as a result.

What we value

  • We are open source - building a huge community around a free-for-life product is key to PostHog's strategy.

  • We aim to become the most transparent company, ever. In order to enable teams to make great decisions, we share as much information as we can. In our public handbook everyone can read about our roadmap, how we pay (or even let go of) people, what our strategy is, and who we have raised money from.

  • Working autonomously and maximizing impact - we don’t tell anyone what to do. Everyone chooses what to work on next based on what is going to have the biggest impact on our customers.

  • Solve big problems - we haven't built our defining feature yet. We are all about shipping fast, talking to users, and iterating.

What you’ll be doing

We are looking for someone to take our analytics capabilities to the next level. You will be working with our Product Analytics small team to iteratively build the next generation of our analytics backbone. 

You’ll be mainly working with ClickHouse and Python, making sure all our queries are “Web Scale”, and that our users are happy. You will help us build HogQL, our own wrapper around ClickHouse SQL. More generally, you’ll proactively work to make our analytics best in class.

If you want to see for yourself exactly the kinds of projects you would be working on, check out:

Requirements

  • You have experience building high-performance data systems.

  • You move fast, have a strong bias for impact and don’t shy away from stepping on toes.

Nice to have

  • You've worked in a high-growth SaaS company and/or analytics product. 

If this sounds like what you’d love to be doing, we can’t wait to hear from you. If you’re not sure that you exactly fit the above criteria, get in touch anyway. Alignment with our values is just as important as experience! 🙏

Salary

We have a set system for compensation as part of being transparent. Salary varies based on location and level of experience.

Learn more about compensation

Location (based on market rates)

The benchmark for each role we are hiring for is based on the market rate in San Francisco.

Level

We pay more experienced team members a greater amount since it is reasonable to expect this correlates with an increase in skill

Step

We hire into the Established step by default and believe there's a place to have incremental steps to allow for more flexibility.

Salary calculator

  1. Benchmark (San Francisco) $236,000
  2. Location factor 1
  3. Level modifier 1
  4. Step modifier 0.95 - 1.04
Base salary$224,200 - $245,440plus equity

Benefits

  • Generous, transparent compensation & equityGenerous, transparent compensation & equity
  • Unlimited vacation (with a minimum!)Unlimited vacation (with a minimum!)
  • Two meeting-free days per weekTwo meeting-free days per week
  • Home officeHome office
  • Coworking creditCoworking credit
  • Private health, dental, and vision insurance.Private health, dental, and vision insurance.
  • Training budgetTraining budget
  • Access to our Hedge HouseAccess to our Hedge House
  • Carbon offsettingCarbon offsetting
  • Pension & 401k contributionsPension & 401k contributions
  • We hire and pay locallyWe hire and pay locally
  • Company offsitesCompany offsites

Get more details about all our benefits on the Careers page.

Your team's mission and objectives

Makers everywhere get better at building products because of PostHog

Q1 2024 Goals

  1. HogQL & Data Exploration (Julian, Marius)
  • Convert ALL our insights to use HogQL as their base.
    • Most product analytics insights are built in a bespoke way using our "legacy" Python codebase. This code produces ClickHouse SQL as its output, and is hard to extend, as all queries mix both platform level concerns (e.g. how "group analytics" works) and query level concerns (most optimal query for this data structure). Adding new query types or new platform features has turned out to be a nightmater with so many loose parts to consider.
    • We've built the HogQL platform, which takes care of implementation details (e.g. where precisely are person properties stored) and lets users focus on writing queries. We're now rewriting all our insights to output HogQL instead of ClickHouse SQL. This will make the system more reliable, fix whole classes of bugs, and allow the end user to directly modify the generated HogQL SQL for further analysis.
    • The migrated queries are also a blocker for the removal of a lot of legacy frontend code, which is often causing bugs.
  • Improve the type system and get rid of assumeNotNull.
    • ClickHouse is notoriously cranky when it comes to NULL-s. Whenever it sees any unaccounted null anywhere, the entire row is discarded from analysis. We have several fields and properties, which are sometimes NULL, but mostly not. We have special handling for nullable fiels in the concat function, and in all compersions. For example (0 != NULL) feels like it should return true, but in ClickHouse it returns NULL. In HogQL it returns true due to our special handling.
    • This special handling in HogQL makes for better predictable queries, at the cost of some performance. We can optimise this further if we know a field to definitely not be NULL. Unfortunately this nullability information gets lost once fields pass functions and subquery boundaries. Upgrading the type system to account for this is the goal.
  • Write great docs for HogQL and data exploration nodes.
    • Make sure all Data Exploration Nodes, including HogQLQuery, are documented somewhere.
    • Can we build a live API playground?
  • Proactively monitor query performance.
  1. Product Analytics frontend (Thomas, Michael)
  • Clean things up now that we have PostHog 3000 and HogQL everywhere.
    • Migrate Insights in the database away from "filters" onto "query"
    • Purge legacy UI
    • Purge legacy python insights
  • Prioritise and work on any of the many ideas we have to make the app better:
    • Universal Exploration view
    • Reworked filtering experience
    • Query builder 3000
    • Notebook-first flow
    • Make Product Analytics as easy as Web Analytics
  1. BI (Tom)
  • Support non-event data sources on HogQL insights.
  • Build the new querying experience, and/or integrate it into the "Explore" view.

Action plan:

  • Come January, we'll take this list, split the checkboxes between the team, and keep going till it's done. ETA: end of January.
  • In February (leap year 🎉), we'll make Product Analytics ~great~ spark joy again: insights UI cleanup, unified data exploration experience, adding missing analysis features (lifecycle breakdowns, etc), and in parallel work on the BI and the HogQL editing experience. What exactly we'll do and in what order is still TBD.
  • In March we'll keep going. The goal is to have an amazing BI / Product Analytics / Insights / Explore / HogQL experience by the end of it.

Interview process

We do 2-3 short interviews, then pay you to do some real-life (or close to real-life) work.

  • 1
    Application(You are here)

    Our talent team will review your application to see how your skills and experience align with our needs.

  • 2
    Culture interview30-min video call

    Our goal is to explore your motivations to join our team, learn why you’d be a great fit, and answer questions about us.

  • 3
    Technical interview45 minutes, varies by role

    You'll meet the hiring team who will evaluate skills needed to be successful in your role. No live coding.

  • 4
    PostHog SuperDayPaid day of work

    You’ll join a standup, meet the team, and work on a task related to your role, offering a realistic view of what it’s like working at PostHog.

  • 5
    OfferPop the champagne (after you sign)

    If everyone’s happy, we’ll make you an offer to join us - YAY!

Apply

(Now for the fun part...)

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