Principal Technical Product Manager, Data Platform
New
Based in the United StatesFull-TimePrincipal
SalaryCompetitive base salary with performance-based incentives or bonuses where applicable. Equity participation opportunities.
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Job Details
- Experience
- 5+ years of product management experience
- Required Skills
- ETLProduct Management
Requirements
- 5+ years of product management experience, with significant experience working on data platforms, data infrastructure, or data governance products.
- Strong understanding of ETL/ELT pipelines, data catalogs, metadata management, and data lineage or provenance tracking.
- Experience designing developer-facing APIs, ingestion frameworks, or technical tooling.
- Proven ability to define and implement data governance strategies, including access controls, sensitivity classification, and usage restrictions.
- Ability to transform complex, cross-functional data challenges into scalable and measurable product solutions.
- Strong technical judgment and ability to collaborate effectively with engineering teams on architecture and implementation decisions.
- Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
- Excellent communication skills with the ability to influence technical and non-technical stakeholders.
Responsibilities
- Define and own the data platform roadmap, including data ingestion, automated detection, schema reconciliation, and lineage capabilities.
- Lead the development of ingestion workflows and templates that allow external research partners and internal teams to efficiently integrate high-quality data.
- Design product experiences for automated data matching, reconciliation, and validation to ensure datasets are ready for downstream AI and scientific applications.
- Establish approaches for dataset provenance, sensitivity classification, access controls, and field-of-use governance.
- Partner with engineering, scientific teams, and stakeholders to define experiment integration APIs and scalable data management solutions.
- Build and manage federated data-sharing capabilities that enable secure collaboration while protecting intellectual property.
- Define success metrics such as dataset usability timelines, matching accuracy, governance adoption, and lineage completeness.
- Translate complex technical and scientific challenges into clear product priorities, measurable outcomes, and actionable roadmaps.
- Drive alignment across engineering, science, design, compliance, and customer-facing teams through strong communication and product leadership.
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