Sr. Product Manager

Applied Systems Canada•Toronto, ON

2d•CA$110,000 - CA$160,000•Hybrid

About The Position

We are looking for a Senior Product Manager to own the product vision, strategy, and roadmap for our internal data lake. This is a high-impact, cross-functional role at the heart of our data organization - you will define how the company collects, governs, and derives value from its data assets, partnering closely with Data Engineering, Data Science, Analytics, and business stakeholders to build a best-in-class platform on Google BigQuery. This role demands both strategic thinking and operational depth - balancing long-term platform vision with near-term execution, navigating competing stakeholder priorities, and ensuring data quality, privacy, and governance are first-class concerns. To keep us headed in the right direction, we’re looking for people who understand winning is a team sport, who value and seek to learn from our team’s diverse experiences and backgrounds, who welcome a challenge and take risks in the pursuit of creating better outcomes for our customers, and who can, at any given time, step back to laugh and have some fun.

Requirements

7+ years of product management experience, with at least 2 years focused on data platform, data infrastructure, or analytics products.
Demonstrated ability to manage complex, multi-stakeholder environments with competing priorities at senior levels.
Strong understanding of modern data stack concepts: data lakes, warehouses, ELT pipelines, data catalogs, and governance frameworks.
Hands-on familiarity with Google BigQuery
Ability to engage credibly with data engineers and data scientists on technical architecture decisions; excellent communication skills for executive audiences.

Nice To Haves

Experience implementing governance frameworks: data mesh, data contracts, or metadata management tools (Dataplex, Collibra, Alation).
Familiarity with ML platform concepts: feature stores, model registries, training pipelines (Vertex AI, MLflow).
Background in structured and semi-structured data across diverse source systems (CRM, ERP, product analytics, third-party APIs).

Responsibilities

Define and own the multi-year data lake product strategy, translating business needs into a prioritized roadmap that balances platform reliability, new integrations, and insight enablement.
Identify opportunities to consolidate data sources and reduce duplication; communicate vision and trade-offs clearly to executive, engineering, and business audiences.
Serve as the primary product contact for data consumers across Finance, Marketing, Operations, Sales, and Engineering - running alignment sessions, managing expectations, and negotiating prioritization with senior stakeholders.
Define and hold the platform team accountable to clear SLAs for data availability and quality.
Own the intake process for onboarding new data sources - evaluating business value, technical complexity, and downstream impact including schema dependencies, data lineage, and fan-out effects on pipelines and dashboards.
Partner with Data Engineering to set ingestion standards and champion data cataloging so every dataset is findable and usable across the organization.
Work with Data Science to prioritize feature store development, training dataset pipelines, and experiment tracking infrastructure based on model roadmap needs.
Ensure teams have reliable, well-documented access to curated datasets, and co-define success metrics that bridge raw data availability to actionable business intelligence.
Build and own a comprehensive governance strategy on BigQuery covering data classification, access control (RBAC/column-level security), retention policies, and audit logging.
Define data ownership models and drive adoption of quality frameworks - profiling, lineage tracking, anomaly detection - while collaborating with Legal and Security.