Senior Product Manager
- Location
- London, United Kingdom
- Work mode
- Hybrid
- Type
- Full-time
- Seniority
- Senior
- Salary
- Not stated
- Department
- Product
- Posted
- 30 Oct 2026
Verified open 3 Nov 2026 · Source: Teamtailor
About the role
Lunio Senior Product Manager
(Measurement & Data)
Reports To: CPTO
Location: UK, hybrid (London)
Role Type: Full-Time, Permanent
About LunioLunio is building a performance marketing platform that helps businesses reduce wasted spend and improve ROI. Our customers are household brands at the cutting edge of digital advertising. Our products directly influence customer performance, retention and growth. We operate with high autonomy, high accountability, and measurable commercial expectations. This team will be working across Data-Science and our Full Stack Engineering team in our Measurement and Data product pillar.
The roleYou will own Lunio’s measurement and data platform, including attribution, identity, pipelines and integrations. You will turn complex marketing data into reliable measurement and commercially valuable products. You will be given high autonomy and accountability for business outcomes. You love working in an environment where you can move from ambiguity to a shipped outcome quickly, and test before you build.
What you will be responsible forOwn the measurement and data product strategy and roadmap. Make build, buy and deprecate decisions that balance customer and commercial value, reuse across customers, and ongoing operating cost.
Own the integrations roadmap across advertising platforms, data warehouses, CDPs and CRMs, including partner relationships and API dependencies.
Lead continuous discovery with customers, commercial teams, engineers and designers. Keep customers involved early and test the highest-risk assumptions quickly.
Have worked directly with engineering teams, demonstrating you can build trust across commercial, engineering and design, bringing people with you without formal authority
Write clear, rigorous specifications (PRDs, acceptance criteria, data and integration requirements) that give engineers clarity on what to build.
Own data-quality and reliability outcomes with engineering: agree customer-facing targets, prioritise improvements by customer and commercial impact, and track results.
Strong understanding of digital advertising, performance marketing and conversion measurement. You understand how platforms such as Google Ads and Meta capture, optimise, attribute and report conversions, and how conversion data flows.
Strong understanding of identity, matching and modern marketing data stacks, including first-party identifiers, identity stitching, CDPs, CRMs and data warehouses.
You understand the limits of attribution, when incrementality testing is needed, and how data quality, identity and privacy constrain what can be claimed. You can judge when excluding traffic or audiences cuts waste and when it costs more opportunity than it saves.
You have owned a data-intensive product or platform capability from customer discovery through production use. You can explain the product decisions and technical trade-offs you owned, the measurable outcomes, and where evidence changed your direction.
You can independently read API documentation, interrogate sample data and trace conversion flows. You work directly with engineers on data models, matching logic and failure cases, challenging options and making informed product trade-offs.
You have owned a platform, API or integrations product in high-growth B2B SaaS with commercial accountability.
You have worked directly with major advertising platforms such as Google Ads, Meta, TikTok or Microsoft Ads, including their APIs and data models.
You prototype with AI tools to test ideas quickly before work enters a sprint.
In your first 6 months, we would expect to see:
An evidence-backed roadmap with clear priorities, success measures and explicit decisions about what not to build.
Shipped capabilities are in production use, with measured impact on an agreed customer or platform outcome and evidence of their commercial contribution.
Data quality and pipeline reliability are measured, reported and improving against a baseline you set.
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