136K–240K CAD / year
Principal Technical Product Manager, Data Platform
ProductRemote — Canada
Published on 2026-11-06
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About this role
Own the data platform powering SandboxAQ’s AI Simulation scientific discovery products across drug discovery and materials design. Lead the full dataset lifecycle, from partner and lab ingestion through governance, scientific use, and evidence export, working as a senior individual contributor across engineering, science, design, and trust/compliance.
About the company
SandboxAQ leverages artificial intelligence and quantum technology to improve decision-making processes across various sectors, including life sciences and medical devices. The company focuses on developing innovative solutions that address complex challenges in data analysis, research, and product management.
The team
AI Simulation (AISim)
Stack
ETL/ELTKnowledge graphsHDF5SDFCSVJSON-LD
What you'll do
- Own the data platform roadmap for ingestion, detection, schema reconciliation, and lineage.
- Set strategy and execution for AISim’s knowledge graph.
- Build ingestion templates and auto-matching experiences for CRO and lab-partner data.
- Drive dataset provenance, sensitivity tagging, and field-of-use governance.
- Define experiment-integration API schemas with BioSim and ChemSim teams.
- Own federated data management for IP-safe partner data sharing.
- Track platform metrics such as time-to-usable, auto-match accuracy, and lineage completeness.
What we're looking for
- 5+ years of product management experience, with depth in data platforms or governance.
- Hands-on familiarity with ETL/ELT pipelines, data catalogs, and provenance or lineage tracking.
- Experience designing developer-facing data APIs and ingestion tooling.
- Experience defining access, sensitivity-classification, and purpose or field-of-use controls.
- Ability to turn ambiguous, cross-team data problems into scalable, measurable products.
- Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
Nice to have
- Experience with scientific data formats such as HDF5, SDF, CSV, or JSON-LD.
- Understanding of federated learning and IP-sharing constraints in R&D.
- Experience designing for research scientists and agents.
- Knowledge of regulated data governance, including HIPAA, FedRAMP, GDPR, SOC 2, or GxP/21 CFR Part 11.
- Experience with audit, evidence-export, or compliance-attestation workflows.
- Familiarity with drug-discovery or materials-research data lifecycles.
- MBA or equivalent business experience.
Benefits
- Equity participation and performance-based incentives or bonuses, where applicable.
- Medical, dental, and vision coverage for employees and dependents.
- Company-matched retirement savings.
- Paid parental leave and family-building benefits.
- Flexible paid time off and company-wide seasonal breaks.