Technical Product Manager, Product Data & Revenue Platforms
- Compensation
- Not disclosed
- Location
- London, England, United Kingdom
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Product
- Posted
Skills
Must have
- Experience in product management for technical, data or platform products; we expect this will usually mean at least four years in relevant roles.
- Experience working on a MarTech team and/or with marketing and commercial stakeholders
- Enough technical depth to work confidently with APIs, schemas, data contracts, ETL or ingestion pipelines, event flows and production systems.
- A track record of turning ambiguous or fragmented stakeholder needs into coherent, deliverable roadmaps without adding process for its own sake.
- Excellent delivery judgement: you can distinguish discovery from execution, define the right level of product work and keep teams moving.
- Experience balancing planned roadmap work with operational demand, technical debt, incidents and reliability improvements.
- Confidence working with commercially accountable stakeholders, including constructively challenging a proposed solution when the evidence supports it.
- Experience working with engineers and data scientists to take models, pipelines or data products from research or prototype into production.
- A practical, low-ego approach. You care about outcomes, dependable delivery and the long-term health of the systems behind them.
Full description
Lyst is a global fashion shopping platform founded in London in 2010 and catering to over 160M shoppers per year. We offer our customers the largest assortment of premium and luxury fashion products in one place, curating pieces from 27,000 of the world's leading brands and stores. In 2025, Lyst joined Zozo, operators of Zozotown, the leading fashion e-commerce platform in Japan. This partnership marks a bold new era for Lyst, as we accelerate our vision and work together to transform the future of fashion shopping through AI and technology.
At Lyst, we obsess over the customer, providing a search and discovery experience which offers inspiration, fulfilment, and personalisation. We believe that fashion is amazing but shopping for fashion often isn't, and we use our technology, data and creativity to bring more joy, greater choice and fewer fails. Our mission is to help fashion shoppers make better decisions and help fashion partners find better audiences as the category-leading destination for every fashion shopper.
Role
Product data, and the systems used to transform and enrich it, sit at the heart of how Lyst serves customers and grows revenue. We are looking for a technically strong Product Manager to lead the direction and delivery of the platforms that support our affiliate operations, paid marketing and product-data enrichment.
You will work across two connected missions. The first is helping our commercial teams launch and improve high-value capabilities such as channel integrations, product feeds, conversion and cost data, attribution, reporting and ROAS optimisation. The second is improving the quality, reliability and discoverability of Lyst's product catalogue through internal tooling, product data enrichment, merging and deduplication, leveraging our partnership with our Data Science team in New Zealand.
This is not a conventional consumer-facing Product Manager role. Many requests will arrive with a clear commercial goal and a proposed solution. Your job is to use judgement: move quickly when the problem and solution are well understood; challenge, simplify or productise the request when that will create more value; and make the trade-offs visible when BAU, reliability, technical debt and roadmap work compete for the same capacity.
What you'll do
- Own the joined-up roadmap for the Affiliate Operations team, Commercial Enablement and Product-Data Enrichment, with clear outcomes, sequencing and measures of success.
- Turn commercial priorities into well-shaped technical work, partnering with stakeholders who may already have a strong view of the solution.
- Decide when a request should be delivered directly, when assumptions need testing, and when repeated one-off work should become a reusable platform capability.
- Partner with the Engineering Lead and team to clarify scope, dependencies and acceptance criteria, maintain a healthy backlog and improve delivery predictability.