Data Engineering Lead
On-siteToronto, Ontario, Canada
Job Summary
Lead the design, build, and operation of secure, highly scalable end-to-end ETL/ELT pipelines and orchestration workflows while defining data architecture, modeling standards, and governance practices. Establish engineering excellence by enforcing best practices for code review, version control, testing, and CI/CD deployment, and monitor pipeline health to lead rapid incident diagnosis. Optimize cloud infrastructure storage patterns, lifecycle policies, and cost management, then automate manual workflows to reduce technical debt and boost team productivity. Manage a cross-functional team through agile delivery frameworks, mentor peers, and communicate technical concepts to business stakeholders. Requires 8+ years of data engineering experience with 3+ years in leadership, Snowflake expertise, and SAP integration knowledge.
Required Qualifications
- 8+ years of progressive data engineering/platform experience
- 3+ years in a technical leadership, team lead, or people management role
- Proven expertise with enterprise-scale cloud data platforms
- Hands-on Snowflake experience
- Working knowledge of Azure or GCP
- Deep experience guiding technical teams through agile delivery frameworks and modern DevOps workflows
- Expert-level SQL
- Expert-level Python
- Deep hands-on experience with orchestration and deployment tools (e.g., Apache Airflow, Azure Data Factory, Git, and CI/CD frameworks)
- Strong grasp of data modeling methodologies (Dimensional, Star Schema, Data Vault)
- Strong grasp of data observability/quality frameworks
- An exceptional communicator who can confidently translate technical concepts for business stakeholders, navigate ambiguity, and hold a team accountable for high-quality, on-time delivery
Desired Qualifications
- Strong preference for candidates coming from a Retail or E-commerce environment
- Experience extracting/transforming data from SAP modules
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