Salary Range: $140k $175k CAD per annum Job Class: Full Time Work Location: Hybrid, Toronto About the Company: WELL Health is an innovative technology enabled healthcare company whose overarching objective is to positively impact health outcomes by leveraging technology to empower and support healthcare practitioners and their patients. WELL has built an innovative practitioner enablement platform that includes comprehensive end to end practice management tools inclusive of virtual care and digital patient engagement capabilities as well as Electronic Medical Records (EMR), Revenue Cycle Management (RCM) and data protection services. WELL, uses this platform to power healthcare practitioners both inside and outside of WELLs own omni-channel patient services offerings. WELL, owns and operates Canada''''s largest network of outpatient medical clinics serving primary and specialized healthcare services and is the provider of a leading multi-national multi-disciplinary telehealth offering. WELL, is publicly traded on the Toronto Stock Exchange under the symbol ''''WELL''''. To learn more about the company, please visit: www.well.company. Position Summary: As the Senior Data Architect, you are the architectural authority and handson delivery leader responsible for defining the targetstate data architecture and driving implementation outcomes. You will lead engineers directly and operate through crossfunctional squads when needed. You will make architecture decisions, set enforceable standards, review and approve designs, and ensure the platform is delivered with high quality, security, governance, and scale. The current enterprise standard is Snowflake, but we are open-minded and will evaluate alternative components or stacks when there is a clear longterm strategic advantage (e.g., cost, scalability, developer velocity, governance, interoperability, AI enablement). What you will be doing: 1) Architectural Authority & Standards Own the endtoend architecture of the WELL Intelligence Platform and other strategic data products, as directed by the CDAIO. Define architecture principles, reference patterns, and guardrails (batch/streaming, modeling, security, governance, observability). Maintain Architecture Decision Records (ADRs) and lead architecture reviews. Provide final technical approval on critical platform designs; stop/redirect implementations that violate standards. 2) Engineering Leadership & Delivery Ownership Lead data/platform engineers directly (technical direction, planning, prioritization, mentoring, performance feedback as applicable). Drive delivery via squads: align crossfunctional teams (Cloud, Security, Apps, BI/Analytics) around shared outcomes. Own technical execution plans, sequencing, and risk management for platform build phases. Establish engineering waysofworking: CI/CD, code standards, testing, release management, and operational readiness. 3) Data Modeling & Semantic Layer Design and govern conceptual, logical, and physical models. Build and maintain conformed dimensions, canonical entities, and enterprise KPI definitions. Define semantic layer patterns and ownership model so business reporting stays consistent across subsidiaries. 4) Platform Implementation (Handson) Design and guide implementation of ingestion patterns (CDC, incremental loads, eventdriven where appropriate). Define and build reusable data pipeline frameworks, orchestration patterns, and data contract approaches. Drive performance/cost optimization (partitioning, clustering, workload management, rightsizing). Establish platform observability: lineage, monitoring, alerting, SLOs/SLAs, and incident runbooks. 5) Governance, Security, and Privacy by Design Embed privacy/security controls into architecture: least privilege, encryption, auditing, environment segregation. Define patterns for row/columnlevel security, tokenization/masking, secure data sharing, and policyascode where possible. Ensure the platform design supports compliance expectations in datasensitive environments (PHI/PII). 6) AI/Automation Readiness Ensure curated datasets are AIready: traceable, reproducible, highquality, and appropriately governed. Define patterns for secure retrieval and controlled access for AI use cases. Collaborate with AI delivery teams to enable automation and agentic workflows without weakening governance. 7) Stakeholder Partnership Translating business needs into a pragmatic backlog of data products and platform capabilities. Align subsidiaries on standards while supporting local realities (source system variance, maturity differences). Communicate tradeoffs clearly: cost vs speed vs quality vs risk. You have: Experience 710+ years in data architecture / data engineering / platform engineering. Proven track record architecting and delivering cloud data platforms endtoend. Demonstrated leadership experience: leading engineers directly and/or leading delivery through squads. Technical Depth Strong expertise with Snowflake (or equivalent modern warehouse/lakehouse) and data platform best practices. Deep skills in data modeling (dimensional modeling; strong conceptual/logical design; pragmatic approach to normalization). Strong orchestration and transformation experience (e.g., ADF/Airflow/Dagster, dbt or similar). Strong SQL; working proficiency in Python. Comfort with APIs, eventing, integration patterns, and secure connectivity across SaaS and internal systems. Familiarity with DevOps practices: Git, CI/CD, InfrastructureasCode (Terraform) collaboration patterns. Governance & Operations Experience implementing scalable data governance: cataloging, lineage, data quality testing, and stewardship workflows. Strong security/privacy fundamentals for sensitive data environments. Leadership & Communication Ability to make decisions, set direction, and drive teams to deliver. Strong coaching and mentoring approach; ability to elevate engineering maturity. Nice to Have Experience enabling AI/ML on a data platform. Experience in multientity / multisubsidiary data platforms or multitenant architectures. Experience in datasensitive industries (healthcare, insurance, financial services). The salary for this position falls within a defined range and will be determined based on several factors, including the candidates experience, qualifications, skills, and the needs of the organization. At WELL, we are committed to fair and equitable compensation and aim to provide a competitive salary that reflects the value and expertise of the successful candidate. WELL, is committed to fostering a diverse, inclusive, and accessible workplace. We welcome and celebrate the diversity of applicants and team members across ability, race, gender identity, sexual orientation, and lived experience. We strive to create an environment where differences are valued and contribute to our collective success this is the WELL Way. This recruitment process uses automated tools, including artificial intelligence, to help review applications. Qualified human decisionmakers review these results and make all final hiring decisions. WELL has been independently certified as a Great Place to Work by the Great Place to Work Institute Canada. This recognition reflects our commitment to building a workplace culture rooted in trust, inclusivity, and employee wellbeing. It also aligns with our Healthy Place to Work pillar and the priorities outlined in our annual Sustainability Impact Report. Want Read more about us: https://stories.well.company/ #J-18808-Ljbffr
Job Title
Senior Data Architect