Senior Manager, Commercial Data Architecture&Governance …, Toronto

Responsibilities

Design, implement, and maintain scalable Snowflake data lakehouse architectures, establishing raw, curated, and analytics zones and optimizing storage and compute performance. Develop ELT/ETL pipelines using Snowpipe, Tasks, Streams, and external orchestration tools for batch and streaming data ingestion.Design and implement dimensional models, data vault architectures, and modern data‑modeling patterns optimized for Snowflake. Lead migration from legacy systems to Snowflake, integrating data from databases, cloud storage, SaaS applications, and real‑time streams while applying reusable, DRY principles.Implement governance frameworks, access controls, data lineage tracking, and compliance with data privacy regulations; monitor and optimize warehouse performance to manage costs. Collaborate closely with data analysts, BI developers, and data scientists to enable self‑service analytics, providing technical guidance and coordinating across analytics groups.Identify new technologies, evaluate opportunities to improve productivity, and develop data and governance roadmaps. Mentor team members and foster a culture of innovation and collaboration within the DI&A team. Qualifications

4+ years of data engineering experience, including 2+ years hands‑on with Snowflake (architecture, tuning, security, and cost optimization). Advanced SQL skills with complex query optimization and Snowflake‑specific features. Experience with cloud data integration tools (Fivetran, Matillion, Talend, or custom solutions) and external staging using Azure BlobStorage, AWS S3, or GCP Cloud Storage.Proficiency in dimensional modeling, data vault, or modern architectural patterns. Programming skills in Python, JavaScript (for Snowflake stored procedures), and shell scripting. Version control and deployment experience with Git, CI/CD pipelines, and infrastructure‑as‑code practices. Nice to Have

Experience with orchestration tools such as Airflow, Prefect, or dbt. Knowledge of Delta Lake, Databricks, or other lakehouse platforms. Experience with streaming data integration using Snowflake Streams, Kafka connectors, or real‑time ingestion patterns. Familiarity with modern data stack tools (dbt, Looker, Tableau) integrated with Snowflake.Multi‑cloud experience across AWS, Azure, and GCP. Snowflake certifications (SnowPro Core, Advanced Data Engineer, or Architecture). Benefits

Work in a dynamic, collaborative, and high‑performing team, engaging on challenging projects that make a lasting impact.

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