Responsibilities :

- Own the backend and platform roadmap for market-data services, real-time pipelines, APIs, the SDK, and the systems behind charts, alerts, and trading; write clear specs and acceptance criteria; and partner with engineering from design through ship.

- Own third-party data integrations end-to-end exchange feeds, broker connections, and market-data vendors; from evaluation through onboarding to production, build the playbook so the tenth integration is faster than the first.

- Manage the provider relationship on the product side scope, data quality, licensing constraints, SLAs, and the day-to-day of keeping feeds healthy (BD owns the commercial deal; you own the technical delivery).

- Make the trade-offs that matter, latency, reliability, cost, and coverage, and defend them with data.

- Run dependency management work across Product and Engineering so backend work is well understood, scoped, and scheduled to unblock other teams, sequenced against US expansion and ROI.

- Treat quality and reliability as product features that define what good means, measure against them, triage data and platform issues with engineering, and close the loop with support and power users.

Requirements :

- 6 to 9 years in product management, with real depth on backend, platform, API, or data-heavy products you've owned; infrastructure/data as a product, not just user-facing features.

- Hands-on experience building OMS (Order Management System) and RMS (Risk Management System).

- Trading, investing, fintech, or financial-data background : you understand market data and the audience.

- You are technically comfortable with APIs, data models, schemas, and latency/reliability trade-offs, and you can hold your own in an engineering discussion (you read specs and schemas natively; you don't need to write production code).

- You have shipped third-party or data integrations end-to-end, evaluating providers, onboarding feeds, and owning data quality in production.

- Strong written communication : you write specs and decisions engineers can build from without a meeting.

- Sharp prioritization : you sequence ambiguous, interdependent work and make defensible trade-offs, and you say no.

- Hands-on operator : you work with engineering, not through layers; you get into the detail and ship.

- Comfortable in a lean, fast-scaling team with high ownership and little hand-holding.

- In-person in our Chennai office.

Nice-to-Haves :

- Worked directly with exchange feeds, broker APIs, or market-data vendors (order book, tick, or OHLC data).

- Familiarity with real-time data infrastructure streaming, websockets, and time-series storage.

- SQL or light scripting to answer your own data questions.

- Payments, billing, or subscription product familiarity is good to have; this surface may come into scope down the line, but it is not a prerequisite.

- FIX protocol exposure; familiarity with Indian (NSE/MCX/SEBI) and US (CME) market structure.

- AI-native workflow : you use modern tooling to multiply your output.

- Top-tier Indian institution (IIT/NIT/IIM) nice-to-have, not a gate.