Principal Technical Product Manager, Data Platform

Accountabilities: Define and own the Data Platform product roadmap, covering data ingestion, automated detection, schema reconciliation, and end-to-end lineage tracking. Lead the strategy and execution of the Knowledge Graph capabilities supporting scientific discovery applications. Develop and manage ingestion templates for contract research organizations (CROs) and laboratory partners, alongside automated data-matching experiences that make incoming datasets usable quickly. Establish dataset-level provenance tracking, sensitivity classification, and field-of-use governance controls. Design experiment-integration API schemas in collaboration with drug discovery and materials design teams. Own the federated data-management product, enabling secure, intellectual-property-conscious data sharing across research partners. Define, monitor, and improve key platform performance metrics, including time-to-usable per dataset, automated matching accuracy, and lineage completeness. Work closely with engineering, scientific, design, and trust and compliance teams to translate complex data requirements into scalable product solutions. Gather feedback from internal users and external partners, ensuring platform decisions address practical research and business needs. Lead through product expertise, cross-functional influence, clear communication, and strong ownership in a collaborative environment. Requirements: 5+ years of product management experience, with strong expertise in data platforms or data governance. Hands-on familiarity with ETL/ELT pipelines, data catalogs, and data provenance and lineage tracking. Proven experience designing developer-facing data APIs and data ingestion tools. Experience defining and implementing data governance controls, including access permissions, sensitivity classification, and purpose or field-of-use restrictions. Ability to translate ambiguous, cross-functional data challenges into scalable products with measurable outcomes. Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. Strong communication and stakeholder management skills, with the ability to influence technical and scientific teams without direct authority. Customer-focused mindset, collaborative problem-solving skills, and the ability to work effectively in a multidisciplinary environment. Highly Desired Qualifications: Experience working with scientific data formats such as HDF5, SDF, CSV, and JSON-LD. Understanding of federated learning and intellectual property-sharing constraints in research and development environments. Ability to design data experiences that serve both scientific researchers and AI agents. Familiarity with regulated data governance frameworks and standards, including HIPAA, FedRAMP, GDPR, SOC 2, GxP, or 21 CFR Part 11. Experience supporting audit processes, evidence exports, or compliance-attestation workflows. Knowledge of data lifecycles in drug discovery, biopharma, or materials research. MBA or equivalent business experience. Benefits: Fully remote position based in Canada. Competitive annual base salary, depending on geographic pay tier: Tier 1 (within 50 miles of Toronto or Vancouver): CA$160,000–CA$240,000. Tier 2 (all other Canadian locations): CA$136,000–CA$204,000. Performance-based incentives or bonuses, where applicable. Equity participation. Comprehensive medical, dental, and vision coverage for employees and dependents, with generous employer premium contributions. Retirement savings plan with company matching. Paid parental leave and inclusive family-building benefits. Flexible paid time off and company-wide seasonal breaks. Flexible work arrangements designed to support work-life balance and sustainable performance. Continuous learning and professional development opportunities, including internal learning programs and cross-functional collaboration. Opportunity to contribute to scientific and technological advances in drug discovery, human health, and sustainable materials.