Data Products - Product Manager (Bangalore East)

Role Overview We're hiring a Product Manager to own the platforms and pipelines that turn raw, often messy data from internal systems and external partners alike into trusted, analytics- and AI-ready assets. This is a horizontal, infrastructure-level role: you own the validation, metadata, quality, and governance layers that other teams build on top of, not a single downstream product. You'll define what "good" data means at each stage of the pipeline, translate that into platform requirements engineering can build against, and work hands-on with the data itself writing SQL, reviewing pipeline output, and validating that standards actually hold up in practice. What You'll Do Strategy & Roadmap - Define the vision, roadmap, and success metrics for the data platform, treating it as a durable strategic asset rather than a one-off project - Identify high-impact opportunities to improve data trust, efficiency, and downstream decision-making - Translate ambiguous platform and business problems into structured plans with explicit milestones Pipeline, Quality & Metadata - Define the stages, validation gates, and quality checks data passes through from ingestion to analytics-ready, and own the platform requirements that make this repeatable across sources, teams, or verticals - Own decisions on what metadata gets generated at ingestion (schema inference, tags, confidence scores, lineage, etc.), at what threshold, and how it's stored and surfaced - Define what "analytics-ready" means, build the tooling that enforces it, and personally validate the data running queries and reviewing pipeline logs, not just monitoring dashboards - Improve how metadata is structured and surfaced to support analytics, governance, and AI use cases Cross-Functional Delivery - Partner with engineering to turn requirements into scalable, well-architected systems, making clear build-vs-buy and technical tradeoff calls - Work with domain and business stakeholders to translate their specific "what does ready/done mean" needs into consistent, reusable platform standards avoiding one-off custom work per team or deal - Act as the connective tissue between business, engineering, and governance functions; hold both a technical and a product conversation in the same meeting Governance, Compliance & Adoption - Ensure the platform meets enterprise standards for data governance, privacy, and security, including handling of sensitive data - Drive adoption of documentation, best practices, and data-integrity standards across teams - Support user enablement (guides, training, communication) and iterate based on feedback and usage data Required What We're Looking For - 34 years of PM experience where the core product was a data pipeline, data quality system, or data platform you've owned the "raw data in, trusted data out" problem end to end - Hands-on technical depth: comfortable writing SQL or Python, reading pipeline logs, spotting schema mismatches, and reasoning through data validation/architecture tradeoffs - Experience with modern data architecture (e.g., lakehouse, data mesh) and the messy realities of ingesting inconsistent data from external or cross-team sources - Strong cross-functional credibility able to write requirements multiple engineering teams and stakeholders can build against, and to work closely with technical teams to drive delivery without being their manager - Solid grasp of product lifecycle management and agile delivery (prioritization, sprint planning, release management) - Excellent written and verbal communication skills Nice to Have - Experience with data quality or metadata frameworks/tooling (dbt, data contracts, catalog tooling) - Familiarity with de-identification approaches for sensitive data (PHI, PII, confidential enterprise data) - Background in a domain where data quality has real downstream consequences (healthcare, finance, etc.) - Exposure to ML training pipelines or AI data workflows - Experience with data governance strategy - Familiarity with modern data platforms/tools (e.g., Databricks, Snowflake, APIs, operational dashboards) Ideal Candidate Profile - Strong analytical and problem-solving skills, comfortable using data to inform product decisions - Genuine interest in the infrastructure that powers enterprise data and AI workloads - Comfortable using AI tools to boost productivity and execution - Growth mindset eager to learn from senior PMs and engineers Role Overview We're hiring a Product Manager to own the platforms and pipelines that turn raw, often messy data from internal systems and external partners alike into trusted, analytics- and AI-ready assets. This is a horizontal, infrastructure-level role: you own the validation, metadata, quality, and governance layers that other teams build on top of, not a single downstream product. You'll define what "good" data means at each stage of the pipeline, translate that into platform requirements engineering can b