Data Engineer, Data & Analytics - 12 months contract

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Metro Supply Chain is a strategic supply chain solutions partner to some of the world’s fastest growing and most reputable organizations. For 50 years, it has excelled at tailoring integrated, data-driven solutions, fueled by advanced systems and technology, that fulfill complex and challenging distribution needs. Managing 19 million square feet operating out of more than 175 sites across North America and Europe with a team of 9,000, it is one of Canada’s largest privately owned supply chain solutions companies. Metro Supply Chain is a 2024 winner of the Canada’s Best Managed Companies program, recognized for its strategic expertise, culture of innovation and commitment to its people and local communities.

SUMMARY

Data engineer is primarily responsible for development and maintenance of data products and pipelines which support BI initiatives across organization. This role is also responsible for designing, developing, and maintaining Snowflake-based data infrastructure solutions to meet the needs of the organization. This role includes designing, building, testing, and deploying scalable, reliable, and secure data pipelines, data lakes, and data warehouses on the Snowflake cloud platform.

RESPONSIBILITIES

• Data Integration and ETL Processes: Design and implement ETL processes to assimilate data from diverse sources, ensuring data quality and consistency tailored to address diverse BI requirements
• Data Modeling and Design: Collaborate with analytics leads, BI & Data analyst to craft a sophisticated data model that captures the intricacies of supply chain analytics & BI requirements.
• Data Warehouse and Database Management: Establish, maintain, and optimize the data infrastructure to support the ever-evolving needs of the cloud (snowflake) platform.
• Data Integrity: Uphold the accuracy of data through systematic quality checks. Work closely with our data engineering team to address any data inconsistencies.
• Data Quality Assurance: Implement mechanisms to guarantee data accuracy, ensuring quick turnaround to data requests.
• Performance Optimization: Monitor system and database performance, implementing refinements that cater to the dynamic demands of the user base.
• Automate and leverage reporting processes from a variety of sources to analyze performance, identify areas of opportunity, and provide actionable insights. Perform Ad-hoc analysis when required to enable fact-based decision making.
• Conduct quality control checks to guarantee the accuracy and precision of deliverables.
• Troubleshoot data visualization issues and propose solutions to rectify errors. Participate in team meetings and provide project progress updates.
• Documentation: Ensure documenting end-to-end data ingestion development across all data pipelines. Uphold meticulous documentation standards for all data procedures and architectural choices.

EXPERIENCE

• 4 years of work experience with development, data warehousing, and end-to-end implementation of Snowflake cloud data warehouse or end-to-end data warehouse implementations on-premises.
• Experience with ETL/ELT, DBT Cloud, SnowSQL, SSIS, stored procedures, Python

• Solid SSIS and SQL skills with exposure to cloud-based platforms (Azure, Snowflake, others) and data science tools (R, Python, Apache Spark, others).
• Reporting & Analysis tools: Microsoft Power BI, SharePoint, PowerApps, PowerFlow, PowerAutomate
• Prior experience with traditional ETL tools like Talend Matillion, Pentaho or similar is a plus.
• Professional experience with APIs and bulk-load patterns to capture data from multiple data sources.
• Deep understanding of data warehousing concepts, including complex data structures, data transformations and data analytics.
• Experience with end-to-end design and build process of Near-Real Time and Batch Data Pipelines, expertise with SQL and data modeling.
• Relevant experience in managing engineering teams to deliver enterprise data solutions using Data Lake, Data warehousing, and Business Intelligence capabilities.
• Technical expertise in the areas of data profiling, data mining and data analytics.

EDUCATION

• University/College degree in Data Science/Analytics, Engineering, or related field
• Cloud certified: Azure Certification preferred