Principal Data Architect, Fsi

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. Within 18 months of our founding in 2021, Snowflake recognized us at the highest partnership tier—a reflection of our deep expertise and impact.
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. And as proud recipients of the Great Place to Work® Certification (2026-2027), we are equally committed to fostering a culture of trust, collaboration, and growth for our people.
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.
Demand for analytical products is outpacing client platforms. 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.
This is a financial services role first. A wrong figure is a client conversation, not a bug ticket. Entitlements are designed in from day one. Messy source data gets reconciled, not papered over. And every decision becomes audit evidence.
You’ll lead project teams assembled per engagement, setting technical direction and carrying proven patterns forward
What you’ll get to do
Client-facing and executive reporting
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
Build reporting that reconciles across sources, including benchmarking and peer comparison where the business needs external context
Self-service analytics for business teams
Give analysts and business users governed direct access to the warehouse so they stop queuing behind data requests
Design semantic and metric layers so key figures mean the same thing in every tool
Support board-level reporting and scenario planning built on the same governed definitions
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
Design product-level cost attribution, monitoring, and alerting so consumption is understood and controlled per analytical product
Produce architecture decision records and control evidence that stand up to audit and client due diligence
Leadership and delivery
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
Plan tasks for self and others, participate in leading engagements, and mentor other engineers
Must-haves
Financial services delivery experience. 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
Entitlement and access design. You've implemented RBAC, row-level and column-level security, and separation of duties in production, not just on a diagram
Deep, hands-on Snowflake Data Cloud experience. You've architected and delivered production solutions on Snowflake, not just used it peripherally
Strong dbt expertise. You've designed, built, and maintained dbt models and transformation workflows at scale
Client-facing credibility. You can hold a room with business or finance leadership and translate in both directions
You’re likely a strong fit if
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
What you’ll bring
Passion for data and engineering excellence
Experience with formal (traditional, modern) 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
Growth expertise: a drive to continuously develop your own skills and those of the people around you
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 vendors, and with third-party data providers common to financial services
Exposure to performance, profitability, or actuarial calculation engines, and to book of record concepts such as IBOR or ABOR
Working knowledge of a control framework or regulatory obligation such as SOC 2, ISO 27001, OSFI B-13, PCI DSS, or NI 31-103, and comfort producing evidence for it
Experience designing data foundations for LLM or agentic workflows over unstructured documents
Speak French fluently
What we work with
Modern Data Workflows (dbt, Airflow, Prefect, Dagster)
Cloud Data Warehouses (Snowflake Data Cloud, Google BigQuery, Databricks Lakehouse, Azure Synapse)
CI/CD (GitLab, GitHub Actions, Jenkins)
Programming Languages (Python, JavaScript, Kotlin or Java)
Visual Analytics (Sigma, Tableau, Looker, Power BI)
Identity and Access (Okta, Entra ID, SSO and SCIM provisioning)
Artificial Intelligence / Machine Learning (Snowflake Cortex, Amazon SageMaker, Azure ML Studio)
Databases (SQL Server, PostgreSQL, MySQL, Oracle, Vertica)
Streaming and Big Data (Apache Kafka, Amazon Kinesis, Apache Spark)
Infrastructure as Code and Containers (Terraform, Docker, Docker Compose)
What’s in it for you? We’re so glad you asked!You will be surrounded by some of the brightest and most accomplished technical minds in our field. We are a team of very diverse and passionate professionals who love working together and solving problems by leveraging technology to help our customers. We pride ourselves in our outstanding work culture that is grounded in our 8 core values: trust, excellence, integrity, humility, accountability, responsibility, kindness, and fun.
We value our people above all, and we provide a competitive compensation and benefits package to show our team our appreciation for everything they do:
We are strong believers of work-life integration and we offer a flexible schedule so that our team can manage their own workload and still be there for family and loved ones.
We offer 4 weeks of vacation annually, in addition to paid personal and sick days, so that our team can unwind, recharge, and enjoy time away for hobbies and family.
We provide a monthly bring-your-own-device allowance for each team member to choose the computer and phone of their preference (and it is theirs to keep afterwards).
We strongly believe in professional growth, so we are continuously educating ourselves with regular lunch & learns and industry events, and we invest in professional development and industry-based certifications for everyone in our team.
We constantly encourage everyone to step outside of their comfort zone and try new things, so we dedicate time each month to work on non-client work and collaborate on new innovative ideas, and we reward people who experiment and take risks.
We enjoy getting together, and we promote co-working days and social events in our main locations on a regular basis.
We are committed to creating a diverse environment and are proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, or age. Please note that you must be legally eligible to work in Canada to be considered for employment, and if selected, you must complete a criminal and credit background check to be hired.
Compensation for this role depends on various factors, including seniority, skill level, and location. Compensation structures may also differ based on the type of engagement—contract rates vary from full-time employee salary ranges. Specific details will be discussed during the hiring process.
We look forward to getting to know you!
infostrux.Com/careers | Join Infostrux, where we design scalable, cloud-based data solutions that enable faster, smarter, data-driven decisions.*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.
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