About Pinpoint
Pinpoint builds and sells software that helps in-house recruitment teams attract, hire, and onboard the right people. Its data platform supports internal tools and reporting, as well as customer-facing resources such as RecTrends, a public benchmarking site.
Responsibilities
•Set the data strategy and guidelines for building with and using data, ensuring teams work from trusted sources and keeping the strategy current as priorities shift
•Shape data requests from senior leadership, assess their value, and deliver the most valuable solutions
•Own the data behind a new customer-facing initiative, identify missing data, and integrate its outputs into the customer intelligence platform
•Provide product managers with tools to access product usage data themselves and engage early in product work to ensure the right data is captured
•Give Customer Success, Sales, and Marketing clear views of key insights, including customer risk and growth opportunities
•Own the customer intelligence platform end to end, including its roadmap, and own RecTrends
•Own the data pipeline from source to insight, including monitoring and a data dictionary, and ensure data is clean and documented for safe use by AI tools
•Build machine learning benchmarks from customer data with the AI engineering team over time
Requirements
•Experience owning data strategy or a whole data function at a fast-growing startup or scale-up
•Have designed and built a data stack in a lean team
•Expert SQL and data modelling skills, including Dataform or dbt
•Strong Python skills and experience managing code in version control
•Hands-on experience with BigQuery or a similar cloud warehouse, such as Snowflake, and modern ELT
•Ability to select tools based on merit, cost, and maintainability
•Track record of building data products used by non-technical teams, not just dashboards
•Experience turning raw product usage data into actionable metrics
•Commercial judgement connecting data work to revenue, retention, and strategy
•Ability to explain concepts clearly to senior leaders and non-technical teams, in writing and in person
•Daily use of LLMs and agentic tools, with the engineering depth to identify when they are wrong and make data safe and reliable for them
•The role has no team underneath it; the strategy must be defined and delivered independently
•The role involves close collaboration with non-technical people to deliver and enable internal data products
•Ability to work within budget constraints and ensure projects deliver sufficient value to justify their cost
Nice to have
•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
Conditions
•UK-based role, working UK hours, with team meetups in London every quarter
•Healthcare coverage includes medical, dental, and vision for the employee and their family
•Unlimited holidays
•Unlimited, immediate access to professional counselling via Spill
•401K or pension contributions depending on location
•Equity with long-term upside
•Up to 16 weeks of fully paid parental leave
•Annual learning budget for courses, books, or other growth-related expenses
