Senior Data Engineer

Are you passionate about building modern data platforms and turning scattered operational data into analytics the business actually trusts?

We're hiring a Senior Data Engineer for a full-time permanent position with a fast-growing Canadian consumer goods distributor that is investing seriously in its data, analytics, and AI capabilities.

In this role, you'll design, build, and scale the pipelines, warehouse, and lakehouse architecture that connect ERP, CRM, eCommerce, WMS, and point-of-sale systems into a single trusted source of truth. You'll set the standards for data quality, governance, and observability, partner with stakeholders across Sales, Operations, Supply Chain, and Finance, and lay the foundations that the organization's analytics and AI initiatives will run on.

Who You Are

You're an experienced data engineer who thrives on complex integration challenges. You enjoy designing pipelines, modeling data properly, and leaving every system faster and more reliable than you found it. You're collaborative and clear with technical and business audiences alike, and confident advising teams on the right approach. You take pride in building data the business can trust and in helping others grow their technical skills along the way.

Work Type

• Location: Markham, ON
• Hybrid: 2-3 days per week in the office
• Vacancy Type: This position reflects a new vacancy

What You’ll Do (Your Superpowers) 

• Design, build, and maintain scalable ETL/ELT pipelines and data workflows that the business can rely on daily
• Design and evolve enterprise data warehouse and lakehouse architectures, applying dimensional modeling principles that hold up as data volume and business complexity grow
• Lead integration across ERP, CRM, eCommerce, warehouse management, and point-of-sale platforms, reconciling the structural and semantic differences between systems never designed to work together
• Develop both batch and real-time processing pipelines, serving day-to-day operational reporting alongside deeper analytical work
• Establish and uphold standards for data quality, governance, lineage, and security across the platform, so that trust in the numbers is engineered rather than assumed
• Tune database performance, query efficiency, and cloud consumption, balancing delivery speed against long-term infrastructure cost
• Implement monitoring, alerting, and observability so pipeline issues are identified and resolved before they surface in front of business users
• Work directly with analysts, data scientists, and stakeholders across Sales, Operations, Supply Chain, and Finance to translate open-ended business questions into well-defined data requirements
• Build the scalable, well-governed data foundations that the organization's AI and machine learning initiatives will depend on
• Raise engineering maturity through documentation, code review, version control discipline, and DevOps/DataOps practice
• Mentor junior engineers and help define how the data engineering function is structured as the team scales

⭐ What We’re Looking For (Our Wishlist) 

• 4+ years of progressive experience in data engineering or a closely related discipline, ideally within a fast-moving, commercially driven environment
• Advanced SQL proficiency, including the ability to write, debug, and tune complex queries against large and imperfect datasets
• Strong Python skills applied to data transformation, automation, and pipeline development
• Demonstrated experience building and orchestrating production-grade pipelines using modern transformation tooling such as dbt
• Hands-on experience with cloud data platforms, particularly BigQuery and Azure Fabric
• Practical working knowledge of at least one major cloud ecosystem such as Azure or GCP
• A thorough grounding in data modeling, warehousing concepts, and dimensional design, with a clear point of view on when each approach applies
• Proven experience integrating REST APIs, streaming sources, and third-party SaaS platforms into enterprise data environments
• Familiarity with CI/CD pipelines, Git-based workflows, infrastructure-as-code, and the application of software engineering rigor to data work
• Strong analytical and problem-solving ability, paired with the communication skills to explain technical trade-offs to a non-technical audience
• A demonstrated ability to work autonomously and manage competing priorities without losing delivery momentum

Nice to Have:

• Experience supporting AI/ML workloads, including feature engineering and the preparation of model-ready datasets
• Proficiency with Power BI or comparable modern BI platforms
• Industry exposure to retail, distribution, supply chain, or consumer packaged goods
• Familiarity with event-driven architectures and real-time analytics patterns
• Experience implementing MDM, data governance frameworks, or data catalog solutions

What Makes This Role Exciting 

• Architectural Ownership: The platform is still being defined, which means genuine influence over how it is designed rather than inheriting decisions already made
• Direct Business Influence: The datasets you build inform decisions taken across Sales, Supply Chain, Finance, and the leadership team
• Foundation for Analytics and AI: The organization's reporting and machine learning ambitions rest on the data foundations established in this role
• Scope to Shape the Function: As the team grows, you'll help set the standards, practices, and structure the data engineering function operates by, and mentor the engineers joining it

• Base Salary: $90,000 – $120,000
• Paid Time Off: Competitive vacation and personal days to maintain a healthy work-life balance
• Comprehensive Health Benefits:  Medical, dental, and vision benefits to support your overall well-being 
• Culture & Team: Be a part of a supportive cross-functional team, that thrives on collaboration and innovation, where every member's ideas are valued and contribute to shared goals and success 

Ready to Elevate Your IT Career? Apply Now!

At STACK IT Recruitment, we connect top technical talent with standout opportunities across Canada. If you meet at least 70% of the qualifications, we encourage you to apply - we’d love to chat!

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AI Use Disclosure:

STACK IT uses AI-enhanced tools to support initial candidate screening and interview note analysis. All assessments and hiring decisions remain human-led.