Senior Data Product Manager

 

At Liberis, our mission is to empower small and medium-sized businesses by removing finance as a friction to growth, delivering contextual, embedded financial solutions to support merchants at every stage of their business lifecycle.

 

About the role

 

Liberis is in the middle of a meaningful shift. We started as a single-product business and are quickly becoming a truly multi-product embedded finance company, with different funding structures, revenue models and customer relationships sitting alongside each other in the same portfolio. That complexity creates real demand for better data, better insight and clearer thinking about how all of it fits together.

This role sits at the centre of that challenge. You will own the data and insights product for Liberis, building the foundations that let our commercial, credit, finance and operations teams actually understand the business they're running. That means thinking carefully about the entities in our data model, how products and customers relate to each other, and how those relationships surface in reporting and analysis - and how it eventually all comes out in great dashboards, tools and self-serve capabilities. It also means managing a team of around 10 analysts and engineers and making sure the work they ship is genuinely useful, not just technically correct.

 

What you'll do

 

Your primary job is to help Liberis's commercial decision makers understand the small businesses we serve and how they consider, use and perform across our product range. Doing this well requires a clear conceptual model of the business and a willingness to engage with stakeholders across the business, as well as taste and customer empathy in developing a great insights product including dashboards, insight tools and self-serve capabilities.

You will own the roadmap for our internal data & insight products. Working with stakeholders across commercial, credit, finance and operations, you will define what good looks like and then work with your team to build it. You will run prioritisation, manage the backlog and make decisions about where effort goes. You will also spend a meaningful amount of time in the detail, reviewing data models and dashboards, asking hard questions about definitions, and making sure what we ship is accurate and trusted.

You will partner closely with the engineering side of your team on how data is modelled and structured in BigQuery and dbt, and with analysts on how it gets presented in Looker. You don't need to write production code, but you need enough technical understanding to be a genuine partner in those conversations rather than a passenger. You will also be responsible for continuing to expand our partner-facing reporting, whereby partners gain visibility into their portfolio.

Finally, you will be a leader on Liberis journey to become an AI-enabled company. Data, insights and analytics are a crucial part of that journey and you are expected to lead, innovate and rapidly improve our posture and capabilities at the intersection of data and AI.

 

What we're looking for

 

This role requires someone who can think clearly about complex data structures and translate that thinking into products that non-technical people actually find useful. The ideal person has strong conceptual thinking skills, great product instincts and enough technical depth to earn the trust of the engineers and analysts they work with.

 

Practically, we're looking for:

• Proven experience in a senior data product or analytics product role in a business with real complexity
• A track record of helping commercial teams make better decisions through better data, not just shipping dashboards
• Strong ability to think about entities, taxonomies and relationships in data: what is a customer, what is a product, what does it mean when those things change shape over time - and what are the implications for the insights our business needs
• Hands-on experience with Looker and LookML and familiarity with best practices and scalable approaches to these systems
• Working knowledge of SQL, dbt and BigQuery, enough to engage seriously with how data is modelled and what's feasible, and to express your thinking in code-speak where needed
• Experience managing a mixed team of analysts and data engineers
• Clear, confident communication with senior commercial stakeholders