Senior Product Manager, Data Monetisation

Role: Senior Product Manager, Data Monetisation

About the role

Flipkart is hiring a Senior Product Manager to own product direction for a strategic, partner-facing data product within our data organization — part of Flipkart's broader data monetisation agenda.

This is a Senior IC role with significant scope: you will shape problem definition, roadmap, and delivery for a high-visibility initiative at the intersection of data platform, product experience, data monetisation, and external stakeholders. You will work closely with engineering, data science, analytics, design, legal/privacy, commercial, and GTM partners — and operate with a high degree of autonomy in ambiguous, fast-moving spaces.

What you'll do

Product strategy & ownership

• Own end-to-end product outcomes: problem framing, prioritization, roadmap, and measurable launch/scale milestones
• Translate complex data capabilities into clear, trusted product experiences for external partners
• Define success metrics (adoption, retention, NPS, revenue, ARR/subscription proxies) and run a tight feedback loop with users and stakeholders

Data monetisation & commercialization

• Shape product packaging, tiering, and entitlements that map customer value to monetisation outcomes
• Partner with commercial, category, and GTM teams on pricing hypotheses, launch motions, and upsell paths
• Translate marketplace data assets into defensible, sellable product propositions — without compromising trust, privacy, or governance
• Track and optimize revenue, conversion, and retention alongside product health metrics

0-to-1 → scale

• Drive MVP definition, phased rollout, and iteration from early pilots to broader adoption
• Balance speed-to-market with data quality, governance, and trust — especially at marketplace scale
• Make explicit tradeoffs across scope, freshness, accuracy, and user experience

Cross-functional leadership

• Partner deeply with engineering and data teams on requirements, SLAs, entitlements, and release planning
• Align category, business, ads, and partner-facing teams on use cases, packaging, and GTM readiness
• Navigate privacy, compliance, and access-control constraints as first-class product requirements (RBAC, entitlements, auditability)

Senior PM Craft

• Write crisp PRDs, run effective discovery (FGDs, shadowing, analytics), and maintain stakeholder alignment without over-indexing on consensus
• Mentor junior PMs or contribute to team rituals (PRD reviews, prioritization forums) as needed
• Represent the product in leadership reviews with clear narratives: what we're building, why now, and what we're not doing

What we're looking for

Experience

• 6–8+ years in product management (or equivalent), with meaningful ownership of at least one data, analytics, BI, or platform product
• Track record of shipping B2B or partner-facing products — SaaS, embedded analytics, self-serve reporting, or API/platform experiences
• Demonstrated exposure to data monetisation — packaging, pricing, subscriptions, usage-based models, or revenue-linked product bets
• Comfort operating in 0-to-1 and scale-up phases; not only optimizing mature products

Skills & mindset

• Strong product thinking: problem decomposition, prioritization under constraint, and outcome-oriented execution
• Fluency working with engineers, data scientists, and analysts — you don't need to write SQL daily, but you understand metric definitions, pipeline dependencies, and freshness tradeoffs
• Experience with multi-tenant products: roles, entitlements, onboarding, and packaging
• Ability to work with legal/privacy/compliance as partners, not blockers
• Clear written and verbal communication; comfortable in senior forums

Strong plus (not mandatory)

• Ecommerce, marketplace, retail, or ads analytics context
• AI-assisted product surfaces (NL query, copilot-style UX, explainability) as part of a governed data product
• Experience productizing semantic layers / KPI definitions or self-serve analytics at scale
• Prior work on governed external data sharing (anonymization, aggregation, partner access models)
• Experience defining commercial models for data products (freemium → paid, tiered entitlements, enterprise deals)