Job Description

Alimentation Couche-Tard Inc., (ACT) is a global Fortune 200 company. A leader in the convenience store and fuel space with over 17,000 stores in 31 countries, serving more than 9 million each day customers across its global convenience store and fuel retail network.

It is an exciting time to be a part of the growing Data Engineering team at Circle K. We are driving a well-supported cloud-first strategy to unlock the power of data across the company and help teams to discover, value and act on insights from data across the globe. With our strong data pipeline, this position will play a key role partnering with our Technical Development stakeholders to enable analytics for long term success.

About the role

We are looking for an experienced Analytics Engineer who can work across semantic layer development, data analysis, BI solutions, and production support. The ideal candidate will have a strong understanding of BI platforms and data models, along with the ability to troubleshoot complex data and reporting issues and work with cross-functional technical teams.

This role combines Analytics Engineering and BI Production Support, with responsibilities spanning semantic model development and enhancement, data validation, performance optimization, issue resolution, and ongoing improvement of BI solutions.

Roles and Responsibilities

• Design, develop, maintain, and enhance semantic models and BI solutions
• Build and enhance Power BI and SSAS/AAS models, including measures, relationships, calculations, and business logic
• Translate business requirements into data models, semantic layer solutions, and BI enhancements
• Analyze data using SQL and other tools to identify data quality issues, inconsistencies, and trends Perform data validation and reconciliation across different data layers
• Troubleshoot and resolve issues related to reports, datasets, semantic models, cubes, data refreshes, and underlying data
• Investigate issues across Snowflake/Databricks, ETL pipelines, ADF, and the BI/semantic layer to determine root cause
• Partner with Data Engineering and other technical teams to resolve complex data and pipeline issues
• Perform root-cause analysis and implement sustainable solutions to prevent recurring production issues
• Monitor and improve the performance, reliability, and scalability of BI and semantic models
• Participate in development activities including new functionality, enhancements, model changes, and technical improvements
• Support production BI solutions while continuously identifying opportunities to improve data quality, performance, automation, and maintainability
• Work closely with business stakeholders to understand reporting requirements and ensure business definitions and KPIs are accurately represented in the semantic layer
• Contribute to BI/Analytics Engineering standards, best practices, and architecture discussions

Qualifications and experience

• Bachelor’s degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)
• Master’s degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.)
• 3+ years of experience in Analytics Engineering, BI Development, BI Production Support, or a similar role

Preferred Skills

• Strong hands-on experience with Power BI and SSAS/Azure Analysis Services (AAS)
• Experience developing and maintaining semantic models / analytical models
• Strong SQL skills with the ability to analyze complex data and perform data validation
• Good understanding of dimensional data modeling, business logic, measures, KPIs, relationships, and calculations
• Experience troubleshooting Power BI reports, datasets, semantic models, cubes, and data refresh issues
• Experience with Snowflake and/or Databricks
• Good understanding of ETL/data pipelines and Azure Data Factory (ADF)
• Ability to trace data issues across source, data warehouse, refined/curated layers, and semantic models
• Experience with data quality validation, reconciliation, and root-cause analysis
• Understanding of BI and semantic model performance optimization
• Experience working with incident management and production issues, including investigation, resolution, and prevention of recurring issues
• Ability to collaborate with Data Engineering, Data Architecture, QA, and business teams
• Strong analytical and problem-solving skills with the ability to investigate issues independently
• Strong communication skills and ability to work directly with business users and technical stakeholders

Behavioral Skills

• Delivery Excellence
• Business disposition
• Social intelligence
• Innovation and agility

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