This is a hybrid role based in downtown Toronto, requiring 3 to 4 days of on-site collaboration per week with flexibility for remote work for the remainder of your schedule. About InfostruxInfostrux is one of North America’s fastest-growing data-focused consultancies. We help organizations unlock the value of their data by building modern, cloud-native platforms that power analytics, AI, and machine learning. Our work spans the modern data stack—covering data engineering, architecture, integration, and modelling with Snowflake as one of our core partners. From startups to Fortune 500s across industries like finance, health, gaming, and retail, we design and deliver scalable data solutions that enable faster, smarter, data-driven decisions. Job SummaryAs a Principal Data Architect, FSI, you will own the data architecture on engagements with financial services clients across banking, insurance, capital markets, and wealth management, embedded with their business and technology teams. You’ll build both the products and the access, security, and delivery foundation that makes them trustworthy, deciding how regulated data is modelled, who sees what, and how it flows to decision-makers. Messy source data gets reconciled, not papered over. You’ll lead project teams assembled per engagement, setting technical direction and carrying proven patterns forward Architect reporting products drawn directly from core operational and front office systems, replacing spreadsheet-assembled deliverables Design the calculation and what-if modelling layers on top, covering performance, exposure, allocation, profitability,



and scenario modelling Give analysts and business users governed direct access to the warehouse so they stop queuing behind data requests Data-informed workflow optimization Rewire client and product onboarding onto one clean, governed data flow Restructure recurring operating cycles and their reporting around timely data rather than manual assembly AI-supported workflows Design the data and retrieval foundations for AI applied where the reading and preparation burden is heaviest, including due diligence, document deep dives, legal and transaction review, meeting preparation, and ongoing monitoring Establish how unstructured material is ingested, chunked, secured, and cited so AI output is traceable back to source Foundational architecture, access, and securityOwn the access and security layer everything above depends on: RBAC and entitlement strategy, identity management, row-level and column-level security, and data architecture validation Establish DEV and PROD separation, API-based pipeline frameworks, code release automation, and security hardening as standard practice on the engagement Analyze requirements with both technical and purely business-oriented stakeholders, and present proposed solutions credibly to business and finance leadership Lead implementation efforts, oversee data engineers, and guarantee solution quality from the data architecture point of view Suggest reusable patterns and process improvements to be applied across the organization You've built production data solutions inside banking, insurance, capital markets, or asset and wealth management,



and you can speak to what changed because of the domain Financial data fluency. You are comfortable with the core data of at least one FSI sub-sector, whether that is transactions and balances, positions and performance, policies and claims, or products and clients, and you can pick up the others Deep, hands-on Snowflake Data Cloud experience. You've designed, built, and maintained dbt models and transformation workflows at scale You've been the architect on a data platform at a financial institution, and you've felt the difference between "the pipeline ran" and "the numbers are defensible" You've had to explain your access model to an auditor or a client's risk team You've worked with financial data reconciliation as part of the architecture You like owning the unglamorous foundation as much as the visible product Passion for data and engineering excellence Experience with formal (traditional, contemporary) and less formal data architectures, methodologies, designs, and processes Intermediate technical leadership experience in (ideally multiple simultaneous) technical projects consisting of 4+ people Senior hands-on experience building data solutions using a variety of traditional and big data technologies Intermediate hands-on experience building data solutions in AWS, Azure, and/or GCP Software engineering experience, including CI/CD, release automation, infrastructure as code with Terraform, and containerized workflows with Docker Additional assets Experience integrating core financial systems via API, such as core banking, policy administration, front office and portfolio management, order management, or fund administration platforms Familiarity with market and reference data vendor

📌 Principal Data Architect, Fsi (Winnipeg)
🏢 Infostrux
📍 Winnipeg