Senior Consultant, Data Analytics & Automation - Data Modernization
About The Position
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. We help organizations become data-driven. Will you collaborate with us? Our Team As a Senior Consultant 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!
Requirements
- Bachelor’s degree in Management Information Systems, Computer Science, Business Administration, Data Science, or a related field (MBA considered an asset)
- 3+ years of experience in data architecture, data management, data governance, or data strategy
- 2+ years of experience in consulting or advisory environments
- Technical & Functional Capabilities
- Understanding of enterprise data architecture concepts, including modern data platforms (cloud, lakehouse) and integration patterns
- Working knowledge of data governance and data management frameworks (e.g., DAMA-DMBOK, DCAM)
- Experience supporting data strategy, roadmap development, or operating model design initiatives
- Familiarity with metadata management, data lineage, and master data management (MDM) concepts
- Exposure to data quality management principles and tools
- Tools & Technologies
- Experience or exposure to modern data platforms and tools such as Azure, AWS, or GCP
- Familiarity with tools such as Databricks, Snowflake, Collibra, Informatica, Atlan, or Attacama is an asset
- Professional Skills
- Strong analytical and problem-solving skills, with the ability to break down complex problems into actionable components
- Effective communication skills, with the ability to translate between business and technical stakeholders
- Experience supporting workshops, stakeholder interviews, and cross-functional collaboration
- Ability to work in a fast-paced, team-oriented environment and manage multiple priorities
Nice To Haves
- Relevant certifications (e.g., CDMP, DCAM) are considered an asset
- Experience in regulated industries such as financial services or insurance is a plus
- Willingness to travel based on client and project needs
Responsibilities
- Data Strategy & Architecture Support
- Support the definition of enterprise data architecture vision and strategy aligned to business priorities
- Contribute to current-state assessments of data architecture, platforms, governance, and operating models to identify gaps and opportunities
- Assist in designing target-state data architectures and roadmaps, including modern data platforms (e.g., cloud, lakehouse, data fabric)
- Translate business requirements into data and analytics solutions, ensuring alignment between functional needs and technical design
- Data Transformation & Delivery
- Contribute to the development of data transformation strategies and business cases, including value articulation and implementation considerations
- Support the design and implementation of data governance frameworks (e.g., data ownership, stewardship, policies, and standards)
- Assist in establishing core data management capabilities such as metadata management, data lineage, and master data management (MDM)
- Support data quality initiatives, including defining quality rules, monitoring approaches, and remediation activities
- Analytics & Data Enablement
- Help enable trusted analytics and AI use cases by supporting the design of well-governed and accessible data architectures
- Contribute to data product design, supporting reusable and domain-oriented data assets
- Assist in advising on modern data platforms and tools (e.g., Databricks, Snowflake, Collibra), including architecture and governance considerations
- Client Engagement & Collaboration
- Participate in client workshops and working sessions to gather requirements and align on data priorities and use cases
- Collaborate with cross-functional teams (business, technology, risk) to deliver integrated data solutions
- Support the development of key deliverables such as data strategies, architecture diagrams, governance frameworks, and data glossaries
- Contribute to ensuring alignment with regulatory, risk, and compliance requirements (e.g., data privacy, controls, reporting)
- Practice Development
- Contribute to internal knowledge development, methodologies, and thought leadership
- Support proposal development, research, and client presentations as needed
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
