Product Owner (Data Platform)

GDS is the data backbone of VNGGames: we centralize data from every game studio into one platform and turn it into analytics products - Analytics Hub, Dashboard Builder / Live Artifacts, Monitoring Hub, game performance dashboards, and AI-assisted data exploration tools.
We are not hiring a ticket-writer. We run a lean model where everyone - including the PO - builds, operates, and owns what they ship. What we need is a builder-PO with an explorer's instinct: someone who goes to game studios without being sent, finds the problems worth solving, prototypes solutions with AI coding tools on real data, and hands validated proofs-of-concept to engineers to productionize.
Our flagship internal product (an AI-native analytics playground on top of a Cube semantic layer) was built exactly this way.
Looking further out: by 2027 we intend to consolidate the GPP (Game Publishing Platform) tool suite into a single product for independent game studios. This role is a candidate to help drive that - so we care as much about your product instincts, technical curiosity, and data fluency as your backlog hygiene.
What you'll do:
Own the game-studio problem space - without waiting to be asked
Build your own relationships with game studio teams (liveops, monetization, community, CS). You book the conversations, run the discovery, and decide what's worth prototyping. We expect you to come back from studio visits with prototypes, not just meeting notes.
Develop a point of view on where game publishing is going - LLM agents, semantic layers, self-serve analytics, player-lifecycle automation - and pull those technologies into concrete product bets. You'll be given room to be wrong; passivity is the failure mode here, not a failed prototype.
2. Prototype with AI, transfer to engineers
Use AI coding tools (Claude Code, Cursor, or similar) to turn ideas into working prototypes fast - clickable, on real data - before committing engineering time.
Validate prototypes with real studio users, then hand off to our BE/FE engineers with the context they need to productionize.
3. Own the product lifecycle, end to end
Ramp up quickly on the GDS portfolio (Analytics Hub, Dashboard Builder / Live Artifacts, Monitoring Hub, game dashboards, permission/access model) and become the go-to person for how these tools work.
Inherit the existing roadmap and open user stories (permission-scoped homepages, dashboard accuracy status, monitoring alerts) - with a mandate to re-justify, re-prioritize, or kill items based on what you learn from users. Continuing the plan and challenging the plan are both part of the job.
Run discovery → PRD → delivery: align stakeholders, write docs engineers actually use, follow through to shipped.
4. Operate what you own - and mine it for insight
Handle day-to-day operation of your tools: permission requests, bug triage with product context, cross-team data requests. This isn't overhead - it's your highest-signal source of what to build next.
Maintain portfolio-level knowledge for leadership reporting and clean handovers; supply devs with expected behavior and edge cases so root-causing is fast.
Requirements:
1.Must have:
2+ years as a Product Owner / PM / Technical PM, ideally on data, analytics, or internal platform products.
Evidence of self-directed discovery: you can point to a problem you found and pursued without being assigned it - a stakeholder pain you chased down, a product you proposed, a prototype you built unprompted.
A track record of learning technology on your own: picked up a new tool/stack because a problem demanded it, and shipped something with it. We'll ask for specifics.
Strong data literacy: comfortable with SQL, metrics definitions (retention, LTV, ARPU, conversion), and reading dashboards critically - you can tell when a number is wrong.
Hands-on with AI coding / prototyping tools; you enjoy building, not just specifying.
Structured writing: PRDs, handover docs, and stakeholder updates people actually read.
Ownership mindset: comfortable in a lean team with no PM-of-PMs above you
2.Nice to have:
Gaming or game-publishing domain knowledge (liveops, monetization, player lifecycle).
Basic coding (Python/JS/TS) - enough to modify a prototype, query an API, read a schema.
BI/semantic-layer stacks (Cube, Tableau, ClickHouse/Trino, dbt) or LLM-based products.
Experience taking an internal tool to external customers (0→1 productization).