Intermediate Data Engineer with strong SQL, BigQuery, Airflow, GCP, and data modeling expertise to help transform raw, messy data into clean, trusted datas

Our client is Canada's largest retailer. They are looking for an Intermediate Data Engineer with strong SQL, BigQuery, Airflow, GCP, and data modeling expertise o help transform raw, messy data into clean, trusted datasets

Location: Toronto (Bathurst and Lakeshore) 2 days/week onsite

Start Date: Targeting Mid-End of May

Duration: Until EOY

We’re looking for an Analytics Engineer with strong SQL and data modeling expertise to help transform raw, messy data into clean, trusted datasets. You’ll work in a modern cloud data stack (BigQuery, Airflow, GCP), building scalable models that power analytics, marketing, and business decision-making.

Key Responsibilities

• Build and maintain scalable, reusable data models in BigQuery
• Transform raw data into high-quality datasets for use across the business
• Collaborate with stakeholders to understand data needs and deliver usable solutions
• Write clean, efficient SQL and contribute to code via Git
• Support and debug Airflow workflows; understand Python-based data pipelines
• Help build and maintain a central source of truth in the Customer Data Platform (CDP)

Must-Have Skills & Experience

• Advanced SQL skills and strong understanding of data modeling (e.g., dimensional modeling)
• Experience with cloud data warehouses (BigQuery strongly preferred)
• Familiarity with cloud infrastructure (ideally GCP) and cloud storage concepts
• Ability to read/debug Python and work with Airflow DAGs
• Experience using Git for version control
• Stakeholder-focused mindset and ability to translate data into actionable solutions

Bonus / Nice-to-Have

• Experience with MarTech, CDPs, or customer 360° data use cases
• Familiarity with marketing or fraud analytics workflows