Sr. Data Architect, Enterprise Data Platform, Toronto

Why you’ll love working here

High‑performance, people‑focused culture. Equity, diversity, and inclusion are fundamental. Employees feel valued and empowered to be authentic. Learning and development initiatives include workshops, Speaker Series events, and LinkedIn Learning. Membership in HOOPP’s world‑class defined‑benefit pension plan. 100% company‑paid extended health and dental benefits for permanent employees, including coverage for mental health, gender affirmation, fertility and drug treatment, psychological support, and a health spending account. Parental leave top‑up and a health spending account of $2,500 per year. Optional post‑retirement health and dental benefits subsidised at 50%. Yoga classes, meditation workshops, nutritional consultations, and wellness seminars. The opportunity to make a difference by helping provide a financially secure retirement for Ontario healthcare workers.Job Summary

The Senior Data Architect is responsible for strategy, architecture, implementation, and optimisation of scalable data architecture and data pipelines, with a primary focus on the Snowflake platform. This role owns key Data Platform and Snowflake capabilities including access management, performance and cost tuning, and enablement of AI/ML capabilities. The candidate designs and implements production‑grade data pipelines and data products using Python and PySpark, partnering with business stakeholders and technology teams to deliver secure, governed, high‑performing solutions.What you will do

Work with Investment Management stakeholders to understand requirements and define solutions. Partner with product and domain stakeholders to translate analytical and operational requirements into Snowflake‑first data solutions (schemas, marts, data products, and pipelines). Collaborate with Enterprise Architecture to define target‑state patterns for Snowflake (data modelling, layering/medallion, data sharing, and secure‑by‑design standards) and ensure alignment to enterprise standards.Define and maintain Snowflake platform reference architectures and reusable implementation patterns (onboarding templates, naming conventions, security patterns, data product standards) and socialise them across engineering teams. Drive architecture governance for major data initiatives by documenting architecture decisions and trade‑offs, reviewing designs, and escalating risks or gaps with mitigation plans.Provide technical leadership across teams, mentor engineers on platform best practices, and represent the data platform in cross‑functional forums. Own Snowflake platform configuration and optimisation: warehouses, resource monitors, query profiling, clustering/materialised views, cost/performance tuning.Implement Snowflake access management and security controls (RBAC/roles, grants, least privilege, secure views, masking/row access policies) and support governed subscription/onboarding processes. Design and build scalable data architectures and data products with Snowflake as the core platform, balancing performance, cost, reliability, and governance.Enable AI/ML capabilities by supporting AI/ML agents and governed semantic models for analytics and decisioning. Participate in design sessions and code reviews; troubleshoot production issues end‑to‑end (pipelines, Snowflake objects, workloads) and iterate quickly to restore service and improve reliability.Define and implement consumption patterns for BI and analytics (e.g., Power BI) including semantic models, performance best practices, and governed access to Snowflake‑backed datasets. What you bring

12+ years of proven hands‑on experience as a Data Architect building modern data platforms and pipelines in AWS. 4+ years deep hands‑on Snowflake experience, including access management, data modelling, performance and cost tuning, and platform best practices. Strong experience with Snowflake Intelligence components (AI/ML agents, semantic models) and integration into governed analytics and operational workflows.Hands‑on data engineering experience with Python and PySpark/Spark, building, testing, and operating scalable ETL/ELT pipelines. Hands‑on experience in AWS platform capabilities, particularly Data Architecture components. Strong problem‑solving skills with a focus on automation, CI/CD, IaaC, DevOps practices, and version control.Proficiency in SQL and Python, strong data modelling skills, and a track record of performance optimisation (including Snowflake query tuning and workload management). Experience in data validation, cleansing, and quality checks to maintain data integrity. Ability to thrive in a fast‑moving environment: comfortable with ambiguity, takes end‑to‑end ownership, and can deliver iteratively while maintaining quality and security.Excellent communication and collaboration skills to work with stakeholders and teams. The actual base salary offered to the successful candidate may vary based on multiple factors, including the individual's expertise and level of experience. This role is eligible to participate in discretionary incentive plan(s) subject to the terms and conditions of the applicable incentive plan text.For reasonable accommodation in the recruitment process, please contact us at .

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