Advance the world's information by shaping the future of data ingestion and processing. This role is pivotal in developing and managing the data ingestion platform that powers our global Data Commons Knowledge Graph.

You will be instrumental in defining the product roadmap for data ingestion tooling, overseeing the end-to-end import of public datasets. Responsibilities include managing data processing, ensuring data quality, and defining the data models and ontologies that structure our knowledge graph.

This position requires bridging ambitious long-term technical goals with precise execution milestones. You will foster a collaborative team environment in Bangalore, operating with significant autonomy and driving consensus while ensuring clear communication across time zones.

Develop a scalable, potentially AI-driven product strategy and roadmap for the complete data ingestion pipeline, covering sourcing, landing, schematizing, processing, entity resolution, and storage within our knowledge graph.

Balance ambitious, long-term platform scaling objectives (e.g., 100x ingestion throughput) with pragmatic, near-term execution and clear 6-week deliverables.

Influence and design essential schema models and ontologies to represent complex public datasets cleanly across knowledge graph and relational schemas.

Own product requirements for ingestion tools, schema mapping UIs, automated processors, ETL pipelines, Data Quality, Observability, and Monitoring.

Oversee vendor partnerships with precision, clearly demarcating internal core ownership versus vendor-managed pipeline tasks, establishing clear accountability, and optimizing incentive alignment.

Bachelor's degree or equivalent practical experience is required.

Minimum of 8 years in product management or a related technical role is essential.

Possess 5 years of experience with a direct focus on data pipelines, ETL infrastructure, or backend data systems.

Demonstrated experience in data modeling, schema design, and API-first development is necessary.

Experience with Knowledge Graphs, ontologies, semantic formats (like JSON-LD), and entity resolution frameworks is highly advantageous.

Familiarity with data engineering concepts including ETL, Data Quality, Observability, Monitoring, DataProc, and various database systems (BigQuery, Graph databases, SQL) is preferred.

Ability to leverage product tools, engage with the technical stack, and function effectively as an Infrastructure Product Manager is key.

Exceptional cross-site communication skills are vital. Familiarity with AI/ML platforms, agentic systems, and evaluation systems is a plus.