Senior Data Architect (Toronto)

Salary Range: $140k – $175k CAD per annum.
Job Class: Full Time.
Work Location: Hybrid, Toronto

Position Summary

As the Senior Data Architect, you are the architectural authority and hands‑on delivery leader responsible for defining the target‑state data architecture and driving implementation outcomes. You will lead engineers directly and operate through cross‑functional 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.

Responsibilities

• Own end‑to‑end architecture of the WELL Intelligence Platform and other strategic data products. Define architecture principles, reference patterns, and guardrails (batch/streaming, modeling, security, governance, observability). Maintain Architecture Decision Records and lead reviews. Provide final technical approval on critical platform designs; stop or redirect implementations that violate standards.
• Lead data/platform engineers directly. Drive delivery via squads: align cross‑functional teams (Cloud, Security, Apps, BI/Analytics) around shared outcomes. Own technical execution plans, sequencing, and risk management for platform build phases. Establish engineering ways‑of‑working: CI/CD, code standards, testing, release management, and operational readiness.
• 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 models so business reporting stays consistent across subsidiaries.
• Guide implementation of ingestion patterns (CDC, incremental loads, event‑driven). Define and build reusable data pipeline frameworks, orchestration patterns, and data contract approaches. Drive performance/cost optimization (partitioning, clustering, workload management, right‑sizing). Establish platform observability: lineage, monitoring, alerting, SLOs/SLAs, and incident runbooks.
• Embed privacy and security controls into architecture: least privilege, encryption, auditing, environment segregation. Define patterns for row/column‑level security, tokenization/masking, secure data sharing, and policy‑as‑code where possible. Ensure the platform design supports compliance expectations in data‑sensitive environments (PHI/PII).
• Ensure curated datasets are AI‑ready: traceable, reproducible, high‑quality, 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.
• Translate 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 trade‑offs clearly: cost vs speed vs quality vs risk.

Qualifications

• 7–10+ years in data architecture, data engineering, or platform engineering; proven track record architecting and delivering cloud data platforms end‑to‑end.
• Demonstrated leadership experience leading engineers directly or through squads.
• Strong expertise with Snowflake (or equivalent modern warehouse/lakehouse) and data platform best practices. Deep skills in dimensional, conceptual, and logical data modeling. Robust orchestration and transformation experience (e.g., ADF, Airflow, Dagster, dbt).
• 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, Infrastructure‑as‑Code (Terraform) collaboration patterns.
• Experience implementing scalable data governance: cataloging, lineage, data quality testing, stewardship workflows. Strong security and privacy fundamentals for sensitive data environments.
• Leadership and communication skills to make decisions, set direction, and drive teams to deliver. Strong coaching and mentoring approach.
• Nice to have: experience enabling AI/ML on a data platform.
• Experience in multi‑entity or multi‑subsidiary data platforms or multi‑tenant architectures.
• Experience in data‑sensitive industries such as healthcare, insurance, or financial services.

Benefits

The salary for this position falls within a defined range and will be determined based on several factors, including the candidate’s experience, qualifications, skills, and the needs of the organization. At WELL, we are committed to fair and equitable compensation that reflects the value and expertise of the successful candidate.