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