ANALYSTE PRINCIPAL, INGÉNIERIE DES DONNÉES, CANADA chez Home Depot Canada à Toronto, ON  M3C 4H9

Vous aimez aider les autres à réussir et laisser votre marque? Vous éprouvez de la fierté à guider les clients vers les bonnes solutions pour leurs projets? Si, en plus de cela, vous êtes de nature curieuse et souhaitez acquérir de nouvelles connaissances, envisagez de commencer ou de faire progresser votre carrière chez Home Depot.
Position Overview:  
Our entrepreneurial spirit and innovative mindset, combined with the resources and support of The Home Depot Canada—the world’s leading home improvement retailer—offer a unique opportunity to join a transformative retail disruptor. As we strive to deliver the best interconnected shopping experience for our customers, we invite you to join our rapidly growing and highly skilled Analytics team. 
As a Senior Data Engineer, you will design and build scalable data pipelines to organise, transform, and optimise billions of rows of data for analytics and decision-making. Leveraging Google BigQuery, Python, and retail domain expertise, you’ll deliver solutions that power insights, solve complex problems, and support both short- and long-term strategies. You’ll collaborate closely with business teams and data analysts to gather requirements and translate them into efficient transformations, building tables and views for dashboards to ensure clean, reliable, and high-performance data. 
Our team goes beyond routine reporting; we engage in creative, hands-on work within an empowering environment where every decision is backed by high-quality data. If you’re an innovator passionate about data engineering and reimagining the future of retail, apply today and help shape the next chapter at The Home Depot Canada. 

Key Responsibilities:  
Design, develop, and maintain scalable data pipelines and ETL processes for structured and unstructured data. 

Build and optimise tables and views for dashboards and self-service analytics. 

Gather and translate business requirements into efficient data transformations. 

Collaborate with business teams, data analysts, and technology partners to deliver reliable data solutions. 

Ensure data quality, governance, and performance across large datasets. 

Leverage Google BigQuery, Python, GBQ stored procedures, and retail domain expertise to develop robust solutions. 

Automate processes and implement strategies to improve data quality across the customer experience. 

Aggregate and prepare data for reporting, dashboards, and scorecards. 

Provide data extraction and actionable insights to internal teams and respond to ad hoc analysis requests. 

Drive continuous improvement by identifying process efficiencies and adopting modern data engineering tools and frameworks. 

Effectively convey complex technical information to stakeholders with a business-oriented background, ensuring clarity and alignment with organisational objectives. 

Familiarity with clickstream data and its applications is beneficial. 

 
Competencies:  
Data engineering: designing and maintaining scalable data pipelines and ETL processes  

Technical skills: proficiency in SQL, Python, Google BigQuery, GCP Dataflow, Pub/Sub, PySpark, Airflow, Vertex AI, Iceberg, Starrocks, Applied AI/ML experience; familiarity with cloud platforms (GCP)  

Business acumen: understanding of retail domain and ability to translate business requirements into data solutions  

Collaboration: strong communication skills and ability to work effectively with cross-functional teams  

Problem-solving: analytical mindset with focus on process optimisation and automation  

Data quality: commitment to accuracy, governance, and performance across large datasets  

 
Skills 
Strong analytical and problem-solving abilities 

Proficiency in data analysis and data engineering concepts 

Excellent organisational and time management skills 

Effective interpersonal and communication skills for cross-functional collaboration 

Ability to manage projects and adapt to change in a fast-paced environment 

 
Direct Manager/Direct Reports:  
Reports to Manager, Interconnected & Marketing Analytics 

 
Travel Requirements:  
Limited 

Travel to the stores quarterly  

 
Physical Requirements:  
Extended Sitting 

Repetitive Tasks 

 
Hybrid Work:  
On site 3 days per week  (Mon, Tue and Thursday)  

 
Working Conditions:  
Office 

 
Minimum Education:  
Bachelor’s degree in computer science, Electrical Engineering, Statistics, Applied Math, or a related technical/quantitative field. 
 
Minimum Years of Work Experience:  
7+ years of experience in data engineering or a related field. 

Proficient in SQL, Python, and one or more big data technologies 

Hands-on experience with Google Cloud Platform (GCP) services 

Familiarity with data warehousing solutions like Redshift, BigQuery, or Snowflake  

Experience building and maintaining ETL pipelines and working with large-scale datasets 

Ability to design and implement stored procedures and optimise complex queries  

Certifications:  
Relevant technical certifications (e.g., Google Professional Data Engineer, AWS Certified Big Data – Specialty, Microsoft Certified: Azure Data Engineer Associate).  

Other Requirements/Assets:  
ITIL Foundation 



The pay range for this position is between $62,200.00 - $70,100.00