Senior/Staff Data Product Manager

<p><strong>Ageras is becoming Shine 🎉</strong></p><p>At Shine, we are redefining how entrepreneurs—freelancers, self-employed professionals, and SMEs—manage their banking and administrative tasks. Through seamless tools and innovative banking solutions, we help them focus on what matters most: growing their businesses.</p><p>Our vision is to become the best friend of every small entrepreneur across Europe. 💚</p><p>Over the years, Shine has grown through the merging of top European FinTechs like Shine (🇫🇷), Kontist (🇩🇪), Tellow (🇳🇱), and more. Today, we’re a team of nearly 500 people.</p><h2><strong><br/></strong></h2><h2><strong>👀 The Data team at Shine</strong></h2><p>At Shine, we're revolutionizing the way entrepreneurs—freelancers, self-employed professionals, and SMEs—manage their banking and administrative tasks. Operating in the ever-evolving FinTech space, we face one of the industry's most intricate challenges: building a robust, reliable architecture to enable seamless data collection, analysis, and visualization. Unsurprisingly, our Data team plays a pivotal role in driving Shine' success!</p><p>Our Data department is organized into three specialized squads: <strong>Data Analytics</strong>, <strong>Data Modelling</strong>, and <strong>Data Platform</strong>, ensuring optimal efficiency and focus.</p><h2><strong><br/></strong></h2><h2><strong>📋 Your role as a Senior/Staff Data Product Manager</strong></h2><p>You own the product vision, roadmap, and outcomes for Data Platform, Data Modelling and Data Analytics. Your mission is to make data a first-class product at Shine: reliable, discoverable, compliant, and easy to use. You partner closely with the <strong>Director of Data</strong>, who co-owns strategy with you and holds technical responsibility and architectural choices. A core part of this role is <strong>teaching and enabling product teams and business teams (Finance, Revenue, and other functions) to self-serve their data needs</strong>, so we scale impact without scaling headcount.</p><p><strong>Your responsibilities will include:</strong></p><ul> <li><strong>Strategy and outcomes</strong><ul> <li>Define and socialize a unified strategy across Platform, Modelling, and Analytics that prioritizes <strong>self-service and data literacy</strong>.</li> <li>Set OKRs for adoption, trust, time-to-insight, and <strong>self-service ratio</strong>.</li> </ul></li> <li><strong>Roadmaps and prioritization</strong><ul> <li>Run a single intake funnel across product/engineering and business teams.</li> <li>Translate inputs into three coordinated roadmaps built with with the teams: <ul> <li><strong>Data Platform:</strong> ingestion, storage, orchestration, catalog/portal, permissions, quality, <strong>self-serve tooling</strong> for Engineering teams.</li> <li><strong>Data Modelling:</strong> domain contracts, core model evolution, lineage, governance.</li> <li><strong>Data Analytics:</strong> curated KPI layers, standardized dashboards, statutory reporting, <strong>self-serve analytics</strong> for everyone.</li> </ul></li> <li>Define the strategy with the Director of Data and execute it with the Data Engineering Managers. Support the Data Engineering Managers to implement it.</li> <li>Share and communicate the strategy and roadmaps with stakeholders (quarterly OKRs and adhoc communication).</li> </ul></li> <li><strong>Enablement and self-service at scale</strong><ul> <li>Treat the org as customers; define personas and journeys for PMs, engineers, analysts, Finance/Revenue users.</li> <li>Ship <strong>enablement packages</strong>: starter datasets, dbt models, analytics templates (for Omni/Looker Studio/Metabase/…), query patterns, and event schemat.</li> <li>Stand up <strong>office hours</strong>, champions network, documentation hub, “how-to” guides, and short courses on data contracts and tooling.</li> <li>Replace ad-hoc analyst requests with <strong>guided self-service</strong> and SLAs for truly bespoke needs.</li> </ul></li> <li><strong>Team efficiency</strong><ul> <li>On a daily basis, you work and support the Data Engineering Managers and their team to foster efficiency and effectiveness: <ul> <li>suggest practices, processes, (AI) tools, rituals…</li> <li>knowledge sharing</li> <li>assist them with collaboration with other teams and prioritization.</li> </ul></li> </ul></li> <li><strong>Discovery and specification</strong><ul> <li>Lead discovery on high-value use cases; write PRDs/data product specs with contracts, SLAs, and success metrics.</li> <li>Champion “data as a product” across all three teams.</li> </ul></li> <li><strong>Execution and communication</strong><ul> <li>Run planning and reviews; keep delivery predictable and visible.</li> <li>Publish a living roadmap and monthly impact updates with adoption and self-service metrics.</li> </ul></li> <li><strong>Data governance</strong><ul> <li>Lead the tracking strategy to be implemented by Product Engineering teams.</li> <li>Ensure dat