We are seeking a senior, hands-on Data Engineering Lead for one of our clients to oversee enterprise data engineering, platform development, and team mentorship. In this role, you will lead a cross-functional team to design, build, and operate secure, highly scalable end-to-end ETL/ELT pipelines, manage cloud infrastructure, and establish engineering excellence across the organization. We are looking for someone that is passionate about all things data, but also enjoys team management and helping their peers grow, develop, and work towards various organization goals as a cohesive team.

Technical Leadership & Pipeline Engineering

- Pipeline & Architecture: Lead the design, operation, and optimization of scalable ETL/ELT pipelines and orchestration workflows. Define and maintain data architecture, modeling standards, governance, and data lineage practices.
- Engineering Standards: Establish and enforce team best practices for code review, version control, testing, and CI/CD deployment to ensure high-quality, well-documented outputs.
- Platform & Cost Optimization: Monitor pipeline health and infrastructure performance to lead rapid incident diagnosis. Optimize cloud data platform storage patterns, lifecycle policies, and cost management.
- Continuous Improvement: Automate manual workflows, actively reduce technical debt,



and evaluate emerging tools and technologies to boost team productivity.

Required Experience & Background

- Professional Experience: 8+ years of progressive data engineering/platform experience, including 3+ years in a technical leadership, team lead, or people management role .
- Industry Background: Strong preference for candidates coming from a Retail or E-commerce environment.
- Cloud & Platform Mastery: Proven expertise with enterprise-scale cloud data platforms. Hands-on Snowflake experience is required, alongside working knowledge of Azure or GCP.
- Agile Delivery: Deep experience guiding technical teams through agile delivery frameworks and modern DevOps workflows.
- Languages & Frameworks: Expert-level SQL and Python . Deep hands-on experience with orchestration and deployment tools (e.g., Apache Airflow , Azure Data Factory , Git, and CI/CD frameworks).
- Data Design: Robust grasp of data modeling methodologies (Dimensional, Star Schema, Data Vault) and data observability/quality frameworks.
- Soft Skills: 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.
- SAP Integration: Experience extracting/transforming data from SAP modules is ideal

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📌 Lead Data Engineer (Toronto)
🏢 Hire DigITalent
📍 Toronto