Senior Data Engineer
- Toronto, ON
- Hybrid
- Posted Sep 18, 2026
- 1 position
Opens an external site
- Employment type
- Contract
- Experience level
- Lead · 10+ years
- Minimum education
- Bachelor’s degree
- Apply by
- Oct 11, 2026
- Posting language
- English
- Working hours
- 40 hours per week
- Office presence
- 1 days per week
- Seniority
- Mid-Senior level
- Application method
- Direct apply is available
Job summary
Design and optimize scalable data pipelines using Medallion Architecture within GCP to support sales and inventory domains. Provide technical leadership and mentorship to junior and mid-level engineers while managing stakeholder requirements.
Job details
Senior Data Engineer Contract position, 4-Month Contract initially with possible extension Number of positions: 1, hybrid role, 1-2d/m in office for now Location: North York, ON Must be eligible to work in Canada Roles and responsibilities: We are seeking an experienced Senior Data Engineer to join a high-performing analytics team supporting sales and inventory domains in an enterprise retail environment. In this role, you will design and optimize scalable data pipelines, lead data infrastructure modernization efforts, and provide strong technical leadership. Beyond core technical execution, you will serve as a mentor to junior and mid-level team members, establishing best practices in data governance, advanced data modeling, and GCP architecture. Key Responsibilities Pipeline & Architecture Engineering: Design, build, and maintain scalable ETL/ELT pipelines using a Medallion Architecture (Bronze, Silver, Gold semantic layers) within Google Cloud Platform (GCP). Data Warehousing & Optimization: Optimize Google BigQuery tables, views, and complex stored procedures for high-volume data performance, reporting, and self-service analytics. Modernization & Innovation: Drive secondary data modernization initiatives leveraging modern tools such as Dataplex, GCP Dataform, and Iceberg tables. Team Leadership & Mentorship: Guide, mentor, and upskill a team of onshore/offshore junior data engineers, providing technical oversight and promoting best engineering practices. Stakeholder Management: Translate complex business requirements from non-technical stakeholders into high-performing data models and actionable data assets. Data Governance & Quality: Ensure stringent data governance, reliability, and security across large-scale enterprise datasets. Must-Have Qualifications Experience: 8+ years of dedicated Data Engineering experience, with a proven track record in an enterprise retail or high-volume dataset environment. Core Cloud & Query Stack: Senior-level expertise in Google Cloud Platform (GCP), with advanced mastery of Google BigQuery, complex SQL optimization, and Python. Architecture Design: Hands-on experience designing and implementing Medallion Architecture (Bronze/Silver/Gold layers) and advanced data modeling practices. Mentorship & Leadership: Demonstrated capacity to mentor junior/mid-level engineers and lead technical execution across distributed (onshore/offshore) teams. Stakeholder Communication: Exceptional ability to articulate technical concepts clearly to business analysts, analytics managers, and executive stakeholders. Education: Bachelor’s degree in computer science, Electrical Engineering, Statistics, Applied Math, or a related quantitative field. Nice-to-Have Qualifications Modern GCP/Data Stack: Exposure to or willingness to learn GCP Dataform, Dataplex, and Apache Iceberg tables. Domain Expertise: Experience with clickstream data, web analytics, or retail inventory and sales systems. Orchestration & Compute: Experience with Airflow, GCP Dataflow, Pub/Sub, PySpark, or StarRocks. Certifications: GCP Professional Data Engineer certification or related cloud certifications.
What you’ll do
Design and optimize scalable data pipelines using Medallion Architecture within GCP to support sales and inventory domains. Provide technical leadership and mentorship to junior and mid-level engineers while managing stakeholder requirements.
Requirements
Requires 8+ years of data engineering experience in enterprise retail environments with mastery of GCP, BigQuery, and Python. A bachelor's degree in a quantitative field and proven experience in technical leadership are essential.
Listed skills
- Stakeholder Management · Preferred
- Python · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Google Cloud Platform
- Google BigQuery
- Python
- SQL Optimization
- Medallion Architecture
- ETL/ELT Pipelines
- Data Modeling
- Data Governance
- Technical Leadership
- Stakeholder Management
- Dataplex
- GCP Dataform
- Apache Iceberg
- Airflow
- PySpark
- Data Warehousing
Job areas
- Data & Analytics
- Technology
- Engineering
- Retail
- Logistics
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