Manager, Data Platform(s) Architect, Data & AI

KPMG•Vancouver, BC

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. Are you a talented leader with a proven track record for motivating teams and delivering exceptional client service? Our Data & AI team is one of our fastest‑growing practices, with strong client demand across sectors to modernize data platforms and operationalize AI. Our mission is to help clients harness the full potential of the lakehouse paradigm centered on Databricks - to unlock the power of their data and drive business transformation with trustworthy, secure, and scalable AI. As a member of our team, you’ll work with cutting‑edge technology, tackle complex data challenges, grow your skills, and contribute to business growth and innovation in a dynamic and inclusive environment.

Requirements

8+ years consulting experience leading data engineering, analytics, and AI (data/data platform architecture, design, implementation, and/or support of complex data and application architectures that are scalable and repeatable) initiatives.
Hands‑on Databricks and Fabric expertise across the whole data and analytics continuum.
Cloud proficiency in Azure/AWS/GCP including identity, networking, security, and integration with data services.
Expert skills in SQL, Python, and distributed data processing.
Deep understanding of data management including architecture, data engineering, governance, and data quality.
Strong delivery leadership including estimation, planning, and stakeholder communication.
Ability to translate business needs into technical solutions.
Relevant certifications (Databricks, Fabric or cloud architect).
You have fine-tuned your leadership skills and are comfortable leading diverse teams, overseeing a variety of engagements, as well as managing and coordinating expectations of stakeholders.
You see the big picture both as a consultant and as an internal contributor. You are motivated to create solutions that are practical and cost-effective solutions that are relevant to your clients’ objectives and challenges.
You have developed a reputation as a knowledgeable professional in your area, possess a solution orientated and analytical mindset, and enjoy guiding others through complex and at times ambiguous challenges.
You’re a self-starter that takes initiative to constantly improve your skillset and contribute to the overall performance and success of the practice.
You are an exceptional communicator, both verbally and written, with the ability to deliver professional communications, presentations, reports, and documentation.
You have developed a strong professional brand and presence in the community and enjoy contributing to and participating in events.

Responsibilities

Work with cross functional engagement teams to translate business and analytics requirements into a data, analytics and AI strategy and requirement for the engagement.
Architect and develop overall end-to-end design of data and analytics solutions across Data Lakes, Data Warehouses, Data Lakehouses, pipelines on modern data platforms such as Microsoft Fabric, Databricks and Snowflake (with a focus on the first two) on Azure, AWS and GCP (with a focus on the first) and lead the deployment and delivery of the solution.
Analyze, implement, and resolve issues with existing modern data platforms
Provide mentorship to a team of data engineers, software developers, and data scientists with a focus is on modern data analytics platform.
Lead the design and implementation of CI/CD pipelines for application, data, and AI workloads across environments, ensuring robust automation and operational stability.
Design modern data foundations including streaming/batch pipelines, medallion architecture, semantic layer, and data products.
Lead delivery teams through design, build, testing, and deployment, ensuring quality and operational excellence.
Drive pre‑sales, partner collaboration, proposal writing, responding to RFPs, solution demos, PoCs, and technical storytelling.
Develop accelerators, ingestion frameworks, CICD/MLOps templates, and platform standards.
Own scoping, estimation, and task planning for assigned projects.
Embed data management leading practices, including data architecture design and data modeling, master data/metadata/data security/privacy/data quality management, data operations, data integration and interoperability
Develop accelerators, ingestion frameworks, CICD/MLOps templates, and platform standards.
Own delivery outcomes for client engagements, including timelines, quality, and operational stability
Remaining up to date in new and emerging technologies