Manager, Data Products

Scotiabank•Toronto, ON

2d•Onsite

About The Position

The Manager, Data Products supports the development, delivery, and lifecycle management of governed, reusable data products for the Global Banking and Markets (GBM) business within Scotiabank. The role works closely with business stakeholders, data consumers, engineering teams, and governance partners to translate business requirements into trusted data products that are fit for purpose, well-governed, and aligned to enterprise data standards. Reporting to the Senior Manager, Data Lead, this role is responsible for executing against the data product roadmap, managing day-to-day product activities, coordinating delivery efforts, and driving the adoption and continuous improvement of assigned data products. The role helps ensure data products are discoverable, trusted, scalable, and capable of supporting reporting, analytics, operational, regulatory, and AI-driven use cases.

Requirements

Minimum of 3–5 years of relevant experience, preferably in capital markets, financial services, enterprise data, product management or technology delivery.
Proven experience defining product strategy, building roadmaps and delivering data, analytics or platform capabilities from concept through adoption.
Strong understanding of capital markets products, data flows and business processes; experience with regulatory reporting, trade lifecycle, risk, finance or operations data is an asset.
Mastery / subject matter expertise in data governance leading practices, including data management policies, standards, metadata, lineage, data quality, ownership and certification.
Demonstrated ability to work with senior business leaders, engineers, architects, data modelers and governance teams to solve complex problems through a collaborative delivery model.
Strong analytical skills, including comfort with SQL, data profiling, product usage metrics, dashboards and evidence-based prioritization.
Excellent communication, presentation and storytelling skills, including the ability to engage executive management and translate technical complexity into business value.
Post-secondary education: Graduate degree or equivalent experience in business, finance, computer science, engineering, data, mathematics or a related discipline.
Project / product delivery discipline, with the ability to manage diverse priorities, make trade-off decisions and deliver high-quality outcomes in a fast-moving environment.

Nice To Haves

Demonstrates strong knowledge of capital markets data, including trade, transaction, client, counterparty, instrument, position, risk, reference and regulatory reporting domains.
Experienced in data product management, data analysis, data governance and / or data engineering within a banking or financial services environment, with a focus on translating business requirements into trusted data solutions.
Strong understanding of enterprise data management principles, including data quality, metadata, lineage, business glossary, data modelling, issue management and regulatory compliance.
Capable of collaborating effectively with business stakeholders, data engineers, architects, modelers and governance teams to deliver scalable, governed data products and services.
Strong communication, stakeholder management and problem-solving skills, including the ability to explain data concepts, requirements, issues and outcomes to business and technical audiences.
Experience with Databricks, cloud data platforms, medallion architecture, knowledge graphs, semantic models, Python, SQL, HQL and / or SPARQL is an asset.
Knowledge of AI, machine learning, and generative AI data requirements is advantageous, with experience contributing to the delivery of AI-ready data products that are governed, high quality, and scalable for enterprise use.

Responsibilities

Support the execution of the Market Order (MOR) data product roadmap by coordinating product initiatives and delivering capabilities aligned to business priorities, regulatory obligations, and strategic objectives.
Partner with business stakeholders, Data Stewards, Data Owners, and technology teams to gather requirements, document use cases, define business rules, and translate data needs into actionable product deliverables.
Manage the backlog, priorities, and delivery activities for assigned data products, ensuring requirements, dependencies, risks, and milestones are clearly understood and communicated.
Support the implementation of data governance practices, including metadata management, business glossary development, lineage documentation, data quality monitoring, certification activities, and issue remediation.
Act as a subject matter expert for assigned MOR data domain, providing guidance on data definitions, sourcing, transformations, usage, and controls.
Collaborate with data engineers, architects, modelers, and platform teams to support the design, build, testing, and deployment of scalable data products and data services.
Monitor data quality, service levels, user feedback, and adoption metrics to identify improvement opportunities and enhance the value and reliability of data products.
Maintain product documentation, including business definitions, data dictionaries, data lineage, requirements, operating procedures, and governance artifacts.
Support regulatory, audit, risk management, and compliance initiatives by ensuring data products meet applicable control, governance, and reporting requirements.
Promote adoption and effective use of data products through stakeholder engagement, training, communication, and ongoing support to data consumers.
Deliver assigned data product initiatives on time, within scope, and aligned with business and governance requirements.
Ensure business metadata, lineage, ownership, and data quality controls are maintained and kept current.
Facilitate collaboration across vendors, business, technology, and governance teams to resolve data issues, prioritize enhancements, and support delivery objectives.
Track and report on key performance indicators related to adoption, data quality, availability, operational health, and stakeholder satisfaction.
Identify opportunities to improve data product usability, discoverability, reusability, and operational efficiency.
Contribute to the evolution of Data Office data standards, common data models, governance practices, and the broader data product operating model.
Support the Senior Manager in product planning, stakeholder management, road map maintenance, and strategic initiatives across the GBM data portfolio.