Product Manager, Data Ingestion & Quality

The Product Manager, Data Ingestion & Quality role is responsible for building the product foundation that transforms raw data into trusted, usable, and scalable AI training assets. This role requires 4-7 years of product management experience focused on data pipelines, data quality systems, data platforms, or ingestion infrastructure.

About the role

This is an opportunity to shape critical infrastructure behind AI innovation while solving one of the industry’s most important challenges: access to high-quality training data. The ideal candidate is a technically fluent product leader who enjoys ambiguity, builds from first principles, and takes ownership of impactful outcomes.

Requirements

• 4-7 years of product management experience focused on data pipelines, data quality systems, data platforms, or ingestion infrastructure.
• Proven experience owning products that solve the challenge of transforming raw, inconsistent data into trusted and usable information.
• Strong technical fluency with the ability to write SQL, analyze pipeline outputs, review logs, identify schema issues, and understand data architecture tradeoffs.
• Experience working with external data sources, third-party integrations, or complex data ingestion workflows.
• Ability to evaluate technical solutions, manage vendor decisions, and balance flexibility with scalability in fast-changing environments.
• Strong cross-functional communication skills with the ability to collaborate effectively with engineering teams and technical stakeholders.
• Experience defining product requirements for infrastructure or platform products.
• Ability to investigate data issues directly and validate solutions beyond dashboards and metrics.
• Experience with data quality frameworks, metadata standards, catalog tooling, or platforms such as dbt, Great Expectations, or similar solutions is a plus.
• Familiarity with de-identification approaches for sensitive information, including healthcare data, personal data, or confidential enterprise datasets, is preferred.
• Exposure to ML training pipelines, AI data workflows, data governance, or domains where data quality directly impacts outcomes is advantageous.

Benefits

• High-impact role within a fast-moving, innovative environment.
• Collaborative culture built around ownership, trust, and technical excellence.
• Opportunity to work with ambitious teams solving complex industry challenges.
• Environment that encourages autonomy, experimentation, and continuous learning.
• Chance to influence product strategy and build scalable systems from the ground up.