Product Manager, Enterprise Data Platform

Equitable•Waterloo, ON

1d•CA$110,000 - CA$120,000•Hybrid

About The Position

At Equitable, we believe great things happen when we work together. We’re a Canadian mutual company driven by purpose - putting people first and helping Canadians protect today and prepare for tomorrow. If you’re passionate about making a difference and growing your career in an inclusive and collaborative environment, we’d love to hear from you. Our culture is built on care, passion and curiosity. We put people above all else, strive to be our best and welcome new ideas to deliver positive outcomes. As a Product Manager, Enterprise Data Platform, you will own the end-to-end lifecycle of Equitable’s enterprise DataHub, ensuring the delivery of reliable, secure, and well-governed data products that enable business insights, client servicing, and emerging AI use cases. You will lead cross-functional collaboration across business, data, and technology teams to define priorities, manage the platform backlog, and deliver high-quality data capabilities. In this role, you will identify opportunities to enhance data quality, accessibility, and governance while driving continuous improvement across the platform. You will partner with stakeholders to translate business needs into actionable solutions and help shape a trusted, enterprise-wide data ecosystem. If you enjoy blending strategy, data governance, and execution in a collaborative environment, this is your opportunity to make a meaningful impact. Join one of the region’s top employers and be part of something that truly makes a difference.

Requirements

6+ years of experience in data product management, data platforms, or analytics delivery roles.
Experience working with enterprise data platforms, data lakes, or DataHub environments.
Proven experience managing product backlogs, prioritization, and stakeholder engagement
Strong understanding of data management concepts (e.g., data ingestion, transformation, lineage, and lifecycle management).
Familiarity with Data Governance, Data Quality, and Master Data Management (MDM) practices.
Knowledge of data platform operations, including monitoring, issue management, and performance optimization.
Ability to translate business data needs into technical requirements and user stories.
Demonstrated ability to manage end-to-end data product lifecycle.
Prioritize competing demands based on business value, risk, and dependencies.
Define clear requirements, acceptance criteria, and success metrics.
Experience working in Agile or hybrid delivery environments and strong track record of delivering data products or platform enhancements at scale
Strong ability to engage and influence Business stakeholders, Data consumers and SMEs, and Technology and delivery teams.
Proven ability to communicate complex data concepts in clear, business-friendly language with experience leading change management and communication efforts
Ability to manage data operations, incidents, and issue resolution across a complex ecosystem.
Strong analytical and problem-solving skills with a focus on root cause identification and continuous improvement.
Experience working with cross-functional teams to resolve data quality or platform issues
Understanding of data governance frameworks, policies, and controls.
Awareness of privacy, security, and regulatory requirements related to data.
Ability to balance data accessibility with risk management and compliance
Highly organized with the ability to manage multiple priorities and stakeholders simultaneously.
Proactive, outcomes-driven mindset with strong ownership and accountability.
Collaborative team player with the ability to build relationships across business and technology teams.
Experience with databases and data modelling concepts including data extraction and manipulation using SQL or similar tools (including advanced Excel skills for data analysis); expertise using Power platform suite of tools such as Power Apps, Power Automate, Power BI etc. to build solutions to support/scale Data Management capabilities.
Post-secondary education or equivalent combination of education and experience in the following or related disciplines: Computer Science, Information Systems, Engineering, Business or another relevant field

Nice To Haves

Knowledge of how AI can be leveraged for these capabilities is highly desirable
Knowledge of coding/programming languages (e.g. Python, Java, C#) is an asset.
Experience in Insurance or Financial Services industry is an asset; specifically, familiarity with insurance-specific data models and operational/business processes, with experience in insurance core systems (e.g., policy administration, claims management) is desirable.

Responsibilities

Own the end-to-end lifecycle of the enterprise DataHub, ensuring it delivers reliable, well-governed, and fit-for-purpose data products.
Define and drive the DataHub roadmap, priorities, and backlog aligned to business and data strategy objectives.
Ensure the platform evolves to meet current and emerging business needs and use cases
Manage intake of new requirements, enhancements, and data requests from business stakeholders.
Own and continuously refine the product backlog, including prioritization based on value, risk, and dependencies.
Balance new delivery, operational stability, and technical debt
Oversee day-to-day DataHub operations, ensuring stability, performance, and availability.
Partner with technical teams to manage data access, ingestion issues, job failures, and operational incidents, and monitor platform performance, usage, and adherence to data management controls
Ensure data governance standards, controls, and policies are embedded in DataHub processes.
Oversee Master Data Management (MDM) processes, including Single View logic and enhancements.
Partner with data governance teams to ensure data quality, data catalog/lineage, and compliance requirements are met
Lead investigation and resolution of data issues within the DataHub ecosystem.
Identify and address gaps in controls, processes, and data quality.
Drive continuous improvement through feedback loops, analytics, and operational insights
Collaborate with engineering and data teams to ensure timely and high-quality delivery of enhancements.
Ensure clear requirements definition, acceptance criteria, and success measures.
Support testing, validation (UAT), and rollout of data capabilities
Act as the primary liaison between business stakeholders, data consumers, and technical delivery teams.
Support teams and initiatives consuming DataHub data by driving change management and communication/training related to DataHub updates and releases
Support with the definition and implementation of key performance indicators (KPIs) and metrics to measure the effectiveness of Data Hub service while providing regular reports and insights to management