Head of Data

Hi 👋 I'm Freddie, CFO at Pinpoint.

We build and sell software that helps in house recruitment teams attract, hire and onboard the right people. We're a team of about 100 across the UK, EU and US, with a mature product, strong product market fit and happy customers.

Our data platform already does a lot. It runs on Google Cloud Platform and feeds our internal tooling and reporting, as well as a number of customer facing resources such as RecTrends, our public benchmarking site. What we're missing is someone who owns where it goes next. Right now that falls on me and Luke, our Director of RevOps, which is why we're hiring a Head of Data.

That's where you come in. You'll work right across the business: with product and engineering on the data we capture, with our AI engineering team on what we build on top of it, and with Customer Success, Sales and Marketing on the data they rely on every day. You'll set the data strategy everyone works from.

You'll also work closely with Tom, our CEO, on a customer facing data initiative we haven't launched yet. We'll tell you more when we talk.

What you should know up front

• This is a remote role based in the UK, working UK hours, with team meetups in London every quarter. Our HQ is in Jersey
• You report to me and you're our first data leader. There's no team under you, and that's by design: you set the direction and do the building yourself
• This isn't a pipeline maintenance role with a bigger title, but the pipeline is still yours: month end and our other financial processes can't go down
• A big part of the job is prioritising: questioning requests, weighing their value, and knowing when something is a nice to have
• Our values actually matter here. We hire people who reflect them in how they work, collaborate, and make decisions

• 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, then 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, giving them the tooling to pull the product usage data they need themselves and getting 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
• Bonus: practical ML or statistical modelling on real business problems (benchmarking, scoring or forecasting), event streaming such as Pub/Sub or Kafka, Vertex AI or LLM pipelines, or Fivetran, Hightouch, Segment or PostHog

You may not enjoy this role if

• 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