Manager, Data Analytics & Automation - Data Modernization Architect at KPMG — NeverHard
Manager, Data Analytics & Automation - Data Modernization Architect at KPMG in Toronto, Ontario. Skills: AI, Advanced Analytics, Analytics, Business Intelligence, Client Service. Apply on NeverHard.
Company
KPMG
Location
Toronto, Ontario
Type
full_time
Required skills:
AI
Advanced Analytics
Analytics
Business Intelligence
Client Service
Collibra
Consulting
Data Architecture
Data Fabric
Data Governance
Overview
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, privacy, financial reporting)
Experience advising on cloud and modern data platforms and tools (e.g., Azure, GCP, AWS, Databricks, Snowflake, Collibra, Informatica, Atlan, Attacama)
Strong communication and stakeholder management skills, with the ability to engage senior business leaders and technical teams
Experience facilitating workshops and leading cross-functional teams to align on data vision, priorities, and solutions
Relevant industry certifications (e.g., CDMP, DCAM) are considered a strong asset
Collaborative, growth-oriented mindset with a passion for building and scaling enterprise data capabilities
Willingness to travel locally and internationally based on client and project needs
KPMG Ontario Region Pay Range Information
The expected base salary range for this position is $103,000 to $135,000 and may be eligible for bonus awards. The determination of an applicant's base salary within this range is based on the individual's location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program.
Providing you with the support you need to be at your best
Our Values, The KPMG Way
Integrity
, we do what is right |
Excellence
, we never stop learning and improving |
Courage
, we think and act boldly |
Together
, we respect each other and draw strength from our differences |
For Better
, we do what matters
KPMG in Canada is a proud equal opportunities employer and we are committed to creating a respectful, inclusive and barrier-free workplace that allows all of our people to reach their full potential. A diverse workforce is key to our success and we believe in bringing your whole self to work. We welcome all qualified candidates to apply and hope you will choose KPMG in Canada as your employer of choice.
Adjustments and accommodations throughout the recruitment process
At KPMG, we are committed to fostering an inclusive recruitment process where all candidates can be themselves and excel. We aim to provide a positive experience and are prepared to offer adjustments or accommodations to help you perform at your best. Adjustments (informal requests), such as extra preparation time or the option for micro breaks during interviews, and accommodations (formal requests), such as accessible communication supports or technology aids, are tailored to individual needs and role requirements. You will have an opportunity to request an adjustment or accommodation at any point throughout the recruitment process. If you require support, please contact KPMG's Employee Relations Service team by calling 1-888-466-4778.
AI Usage
Weembrace the use of artificial intelligence (AI) to enhance the candidate experience and streamline our recruitment processes. AI tools may help with organizing applications or surfacing relevant qualifications. However, no hiring decisions are made using AI. Every hiring decision is made by our hiring managers and recruitment professionals, who are equipped with training that empowers them to use these tools responsibly. AI technologies used in our recruitment process undergo detailed risk assessments, including security and privacy requirements, that align with KPMG's Trusted AI framework.
We believe technology should empower human judgment, not replace it. It's one of the many ways we're delivering on our vision of being a technology-first, people-driven firm.