At KPMG in Canada, our people bring their unique perspectives to Canada’s most important challenges. Here, you can build momentum that reaches beyond our business, develop skills for the future, and take ownership of your career with support at every stage. Join a firm where your career can make a difference.
At KPMG, you’ll join a team of diverse and dedicated problem solvers, connected by a common cause: turning insight into opportunity for clients and communities around the world.
Are you a talented leader with a proven track record for motivating teams and delivering exceptional client service?
We help organizations become data-driven. Will you collaborate with us?
Our Team
As a Manager in Data, Analytics and Automation, you will be a part of our Technology Consulting (Data, Analytics and Automation) practice within KPMG. This is a worldwide network of professionals who collaborate on a daily basis to create value from data. Enterprise Data Management integrates and is the connecting link with other data focused advisory services including Business Intelligence, Advanced Analytics, Digital Transformation, Enterprise Solutions and Data Security. We collaborate across service offerings on data driven solutions. And that is why Forrester Research has recently recognized KPMG as one of the most prominent advisory firms in Data & Analytics!
What you will do
- Define enterprise data architecture vision and strategy aligned to business priorities, enabling scalable, AI-ready, and insight-driven organizations
- Lead current-state assessments of data architecture, platforms, governance, and operating models to identify gaps, risks, and transformation opportunities
- Design target-state data architectures and roadmaps, including modern data platforms (e.g., cloud, lakehouse, data fabric) and integration patterns
- Develop and deliver data transformation strategies and business cases, articulating value, investment needs, and measurable outcomes
- Translate business needs into data architecture solutions, ensuring alignment between functional requirements and technical design
- Design and implement enterprise data governance frameworks, including data ownership, stewardship models, decision rights, and policy structures
- Establish core data management capabilities, including metadata management, data lineage, master data management (MDM), and critical data elements (CDEs)
- Lead data quality strategy and remediation efforts, defining quality dimensions, controls, monitoring, and continuous improvement processes
- Enable trusted analytics and AI by designing architectures that support high-quality, well-governed, and accessible data
- Advise on modern data platform adoption, including architecture design and governance for technologies such as Databricks, Snowflake, and Collibra
- Define and operationalize data product architectures, supporting domain-based ownership and scalable, reusable data assets
- Facilitate stakeholder workshops and working sessions to align on data vision, priorities, use cases, and adoption roadmaps
- Support regulatory, risk, and compliance requirements (e.g., privacy, financial reporting, data controls) through architecture and governance design
- Lead end-to-end advisory engagements, including strategy development, architecture design, governance implementation, and future-state definition
- Develop key data artifacts and deliverables, such as data strategies, glossaries, quality frameworks, architecture diagrams, and control models
- Apply industry and technical expertise to solve complex client challenges and drive practical, scalable solutions
- Contribute to business development, including thought leadership, proposal development, and client presentations
What you bring to the role
- Bachelor’s degree or MBA in Management Information Systems, Computer Science, Business Administration, Data Science, or a related field
- 5+ years of experience in data architecture, data management, data governance, consulting, with a track record of delivering data-driven transformation initiatives
- 5+ years of experience in a consulting environment.
- Strong expertise in enterprise data architecture principles, including modern data platforms (cloud, lakehouse), data integration patterns, and scalable design
- Deep knowledge of data governance and data management frameworks (e.g., DAMA-DMBOK, DCAM) and their practical application in complex organizations
- Proven experience defining data strategies, roadmaps, and operating models, aligning data capabilities to business priorities and measurable outcomes
- Ability to translate business strategy into data architecture solutions, bridging the gap between business needs and technical implementation
- Familiarity with metadata management, data lineage, and master data management (MDM) concepts and tools
- Understanding of regulatory, risk, and compliance requirements, particularly within financial services or insurance (e.g., data controls, priva