Senior Product Manager, Data Platform

Position overview

Responsibilities

• Own the vision and roadmap for storage, compute, and analytics workflow systems.
• Define unified self-service access to storage, compute, and platform access.
• Set and maintain reliability for business-critical analytics and AI workloads.
• Make usage, cost, and performance visible to teams.
• Partner with distributed engineering and users to identify problems and prioritize fixes.
• Lead technical discussions, write requirements, and run quarterly planning and prioritization.
• Manage capabilities through launch, migration, and retirement as technologies change.
• Build in security and compliance, including least-privilege, project-scoped access, and environment isolation.
• Track infrastructure trends, assess vendors, measure platform impact, maintain documentation, and support platform teams.

Minimum qualifications

• 4+ years in product management, including scaled infrastructure or platform products such as data platforms, cloud infrastructure, or developer tooling.
• Ability to align cross-functional and globally distributed teams without formal authority.
• Strong stakeholder communication, anticipation of needs, and ability to build agreement with peers and senior leadership.
• Empathy for technical users and ability to translate their problems into product decisions.
• Ability to connect platform choices to business outcomes and cost, performance, and reliability targets.
• Ability to prioritize across competing teams and workloads.
• Technical depth in storage, compute, query engines, and orchestration, including scale, performance, and cost trade-offs.
• Clear communication and ability to drive internal adoption.
• Fluency in product discovery and research- and data-informed product decisions.
• Track record of leading end-to-end delivery, including migrations that move users from retired paths.
• Data-driven approach to measuring platform usage and making decisions.

Preferred qualifications

• Experience with Spark, Trino, or Athena and Kubernetes or EKS.
• Experience with Iceberg or other open table formats, lakehouse storage, or Snowflake warehouses.
• Experience with Airflow, Temporal, Metaflow, DataOps, or MLOps tooling.
• Experience with big-data access management such as Ranger or Lake Formation.
• Experience with platform observability and cost and performance management.
• Experience with Looker, notebooks, or query workbenches.
• Experience leading infrastructure or platform migrations at scale, including multi-region or data-residency requirements.
• Experience with build-versus-buy decisions and vendor assessments.

Salary transparency

• For Canada-based roles, the expected starting base salary is CAD 122,000 to CAD 179,300.
• Offers depend on experience and geographic location and may exceed the stated range.
• Compensation may also include annual cash bonuses, stock grants, and benefits.

Onboarding

• The role may require in-person onboarding and/or in-person identity verification.