Head of Data

• Set the data strategy and the guidelines for how everyone builds with and uses our data, so we all work from the same trusted sources rather than our own versions, and keep it current as priorities shift.
• Be the person senior leadership turns to when an idea needs data: shape it, test its value, and deliver the version that matters.
• Own the data behind our new initiative with Tom, starting with what's missing to build the version customers will see, and get its outputs into our customer intelligence platform (a tool we built in house to understand our customers).
• Work alongside our product managers, not for them: give them the tooling to pull the product usage data they need themselves, and get involved early in product work so the right data is captured.
• Give Customer Success, Sales and Marketing clear, simple views that tell them what matters, like which customers are at risk and where there's room to grow.
• Own our customer intelligence platform end to end, including the roadmap, and RecTrends, our public benchmarking site.
• Own the pipeline from source to insight, with the monitoring and data dictionary that let people trust what they find, and data that's clean and documented enough for our AI tools to use safely.
• Over time, build machine learning benchmarks from our customer data with our AI engineering team.

• Ownership of data strategy or a whole data function at a fast growing startup or scale up, ideally in B2B SaaS
• A data stack you designed and built yourself in a lean team
• Expert SQL and data modelling (Dataform or dbt), with strong Python and code managed properly in version control
• Deep hands on time with BigQuery or a similar cloud warehouse (Snowflake works too) and modern ELT, and the judgement to pick tools on merit, cost and maintainability
• A track record of data products people actually use, including non technical teams, not just dashboards
• Experience turning raw product usage data into metrics people act on
• Commercial judgement that connects data work to revenue, retention and strategy
• Clear explanations for senior leaders and non technical teams, in writing and in the room
• Daily use of LLMs and agentic tools, backed by the engineering depth and strong opinions to know when they're wrong, and how to make data safe and reliable for them

• Practical ML or statistical modelling on real business problems, such as benchmarking, scoring or forecasting
• Event streaming, such as Pub/Sub or Kafka
• Vertex AI or LLM pipelines
• Fivetran, Hightouch, Segment or PostHog

• You want a team underneath you. There isn't one, so defining the strategy and then delivering it yourself has to excite you.
• You'd rather not work closely with non technical people to deliver and enable internal data products.
• You want an unlimited budget. We need to be smart about how we approach projects, so each one delivers enough value to justify the cost.

• Comprehensive healthcare: excellent medical, dental and vision coverage for you and your family
• Unlimited holidays: take the time you need to rest and recharge
• Mental health support: unlimited, immediate access to professional counselling via Spill
• Retirement contributions: 401k or pension contributions depending on your location
• Remote first: work where you're most productive, with flexibility and trust as the default
• Equity with real upside: share in the long term value you help create
• Fully paid parental leave: up to 16 weeks of paid leave for new parents
• Learning budget: annual funds for courses, books or anything that supports your growth

What you're wondering

• Who will I work with? Me, Luke, our Director of RevOps, and Tom, our CEO, on the new initiative. You'll also work closely with Dom, our CTO, and the engineering team, who build the products that produce much of our data, plus our product managers and the Customer Success, Sales and Marketing teams who use it.
• What tools will I use? GCP (BigQuery, Dataform, Pub/Sub, Cloud Functions, Vertex AI), Fivetran (plus other replication on the product side), Hightouch, HubSpot, GitHub, Hex and Vercel. It's a good foundation, not a fixed one: we expect you to challenge it.
• What does success look like? In your first 90 days, you'll own all of our data infrastructure and maintenance, and work out what data we're missing for the new initiative. By the end of year one, everyone gets the data they need quickly from the same trusted sources and knows where to find it, product managers pull usage data themselves, the new initiative has full coverage of the metrics it needs, Tom and the leadership team see you as a proper strategic partner on data, and engineering respects you.
• What's the salary? We'll talk about pay openly in your first conversation with Mike, our VP of Talent.