Sr Data Product Owner

ARR and NRR are the metrics our company steers the business by, and ARR is externally reported through the earnings cycle, analyst days and annual audit. This role is the business facing owner of that reporting domain. You will sit between Finance and the data platform: taking requests from Finance, and company leadership, defining them properly, and delivering the analysis yourself wherever possible rather than passing everything to engineering.

Two things make this role work. First, you can query the warehouse and answer most questions independently. Second, you understand SaaS revenue mechanics well enough to tell a reporting problem from a deal structure problem.

What you will own

Business engagement. Primary point of contact for Finance stakeholders. Intake, requirements definition, prioritisation and communication back. You decide what genuinely needs engineering.

Ad hoc analysis. First line ownership of continuous ad hoc analysis demand on ARR and NRR. This is the largest and most recurring part of the role.

Quarter end close partnering. Working alongside Finance through close: ARR snapshot, bridge reconciliation, variance explanation and sign off support, against immovable dates.

New GTM motion definition. Analysing and defining each new go to market construct (flex, ramp, delayed start) so it can be modelled and reported correctly.

Bridge validation and ARR maintenance. Investigating bridge movements, and model maintenance.

New metric development. Building ARR and NRR reporting that does not yet exist, from definition through to a delivered dashboard or recurring output.

Required skills

1. 10+ years of experience in data analytics, with exposure to revenue analytics, finance analytics or FP&A systems, at least part of it at a public SaaS company
2. Deep working knowledge of SaaS revenue metrics: ARR, NRR, churn, renewals, ATR, bookings
3. Knowledge of Salesforce, including its objects (opportunities, quotes, entitlements, renewals) and how they flow. Practical understanding of deal constructs: ramp, flex, multi year, delayed start, co terming, early renewal
4. Strong SQL. You must be able to query Snowflake independently and read dbt models to trace how a number was built
5. Fluency with AI and LLM tools, used to accelerate technical delivery and to produce analysis ready for presentation
6. Demonstrated business partnering with Finance, including through quarter end close
7. Experience supporting reported figures, where accuracy is auditable
8. Prior data product owner or analytics business analyst role with backlog ownership
9. Experience defining metrics that did not previously exist, not only maintaining existing ones