Senior Product Manager

Equinix•Toronto, ON

41d•CA$131,000 - CA$181,000•Onsite

About The Position

We are seeking a visionary, highly technical, hands-on Senior Data Product Manager to drive the productization of our data assets. In this role, you will own the end-to-end strategy, roadmap, and core delivery of data products that embed analytics and intelligence directly into operational workflows. This position is not about building dashboards or front-end user interfaces; it is about building the underlying data products, logic, and models that fuel real-time execution. You will bridge the gap between complex data infrastructure and business processes. By partnering with data scientists, engineers, and business leaders, you will ensure our advanced analytics, business logic, and AI models deliver immediate, automated, and context-aware value at the exact moment decisions are made.

Requirements

7+ years of Product Management experience specifically owning data products, data platforms, data APIs, analytics engines, or core ML/AI systems
Proficiency in Google Agents, Advanced SQL skills to query complex, distributed data sets, perform ad-hoc analysis, and validate data integrity
Python or R data manipulation tools are sufficient to explore data structures, query databases, and rapidly build functional backend prototype
Deep understanding of modern data stacks, data pipelines (ETL/ELT), data warehousing (e.g. Big Query, Databricks), and API-driven delivery mechanisms
Strong background in B2B sales cycles, pricing strategies, and data segmentation methodologies
Proven ability to collaborate heavily with data scientists, data engineers, and business process owners to translate operational bottlenecks into technical data specifications
Manages stakeholder expectations within and/or across functions
Identifies and proactively includes correct stakeholders and communications effectively
Understands stakeholder needs and builds effective relationships
Utilizes effective methods of communication with stakeholders, varying approach accordingly

Nice To Haves

7+ years experience preferred
Bachelor's degree preferred

Responsibilities

Operationalize Data Products: Embed predictive analytics, logic engines, and intelligence directly into daily business workflows by connecting deep data pipelines to operational systems
Data Product Lifecycle: Proven success defining, launching, and managing core data products, algorithmic engines, data APIs, or embedded analytical systems
Hands-on Prototyping: Actively build early-stage proof-of-concepts, data mockups, or SQL/Python-based logic prototypes to validate data availability, model logic, and workflow integration prior to full engineering scale
Drive Core Core Use Cases: Productize data streams to deliver specific, high-impact business outcomes
Translate Data to Action: Transform raw algorithmic outputs and data tables into structured, actionable, and real-time guidance streams for frontline systems
Continuous Optimization: Monitor data quality, model drift, performance metrics, and end-business impact to iteratively refine underlying logic and intelligence accuracy
Unlock Data Value: Data insights deliver true ROI only when operationalized. You will prevent valuable intelligence from being buried in passive, disconnected reports
Systemize Intelligence: You will eliminate reliance on intuition and static pricing strategies by systematically injecting data-driven recommendations into daily operations
Scale Decision Quality: Your data products will shift enterprise execution from reactive to proactive, ensuring consistent decision quality across all regions, and customer segments

Benefits

Employee Assistance Program
Healthcare coverage that is designed to complement the provincial healthcare system
Life insurance
Disability insurance
Optional benefit plans
Defined Contribution Pension Plan (DCPP)
Group Retirement Savings Plan (RRSP)
Tax-Free Savings Plan (TSFA)
Vacation
Personal time
Various paid holidays