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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 6 million customers each day 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 a Senior Data Engineer with a collaborative, “can-do” attitude who is committed & strives with determination and motivation to make their team successful. A Sr. Data Engineer who has experience architecting and implementing technical solutions as part of a greater data transformation strategy. This role is responsible for hands on sourcing, manipulation, and delivery of data from enterprise business systems to data lake and data warehouse. This role will help drive Circle K’s next phase in the digital journey by modeling and transforming data to achieve actionable business outcomes. The Sr. Data Engineer will create, troubleshoot and support ETL pipelines and the cloud infrastructure involved in the process, will be able to support the visualizations team. Roles and Responsibilities Collaborate with business stakeholders and other technical team members to acquire and migrate data sources that are most relevant to business needs and goals. Demonstrate deep technical and domain knowledge of relational and non-relation databases, Data Warehouses, Data lakes among other structured and unstructured storage options. Determine solutions that are best suited to develop a pipeline for a particular data source. Develop data flow pipelines to extract, transform, and load data from various data sources in various forms, including custom ETL pipelines that enable model and product development. Efficient in ETL/ELT development using Azure cloud services and Snowflake, Testing and operation/support process (RCA of production issues, Code/Data Fix Strategy, Monitoring and maintenance). Work with modern data platforms including Snowflake to develop, test, and operationalize data pipelines for scalable analytics delivery. Provide clear documentation for delivered solutions and processes, integrating documentation with the appropriate corporate stakeholders. Identify and implement internal process improvements for data management (automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability). Stay current with and adopt new tools and applications to ensure high quality and efficient solutions. Build cross-platform data strategy to aggregate multiple sources and process development datasets. Proactive in stakeholder communication, mentor/guide junior resources by doing regular KT/reverse KT and help them in identifying production bugs/issues if needed and provide resolution recommendation. Job Requirements Bachelor’s Degree in Computer Engineering, Computer Science or related discipline, Master’s Degree preferred. 5+ years of ETL design, development, and performance tuning using ETL tools such as SSIS/ADF in a multi-dimensional Data Warehousing environment. 5+ years of experience with setting up and operating data pipelines using Python or SQL 5+ years of advanced SQL Programming: PL/SQL, T-SQL 5+ years of experience working with Snowflake, including Snowflake SQL, data modeling, and performance optimization. Strong hands-on experience with cloud data platforms such as Azure Synapse and Snowflake for building data pipelines and analytics workloads. 5+ years of strong and extensive hands-on experience in Azure, preferably data heavy / analytics applications leveraging relational and NoSQL databases, Data Warehouse and Big Data. 5+ years of experience with Azure Data Factory, Azure Synapse Analytics, Azure Analysis Services, Azure Databricks, Blob Storage, Databricks/Spark, Azure SQL DW/Synapse, and Azure functions. 5+ years of experience in defining and enabling data quality standards for auditing, and monitoring. Strong analytical abilities and a strong intellectual curiosity In-depth knowledge of relational database design, data warehousing and dimensional data modeling concepts Understanding of REST and good API design. Experience working with Apache Iceberg, Delta tables and distributed computing frameworks Strong collaboration and teamwork skills & excellent written and verbal communications skills. Self-starter and motivated with ability to work in a fast-paced development environment. Agile experience highly desirable. Proficiency in the development environment, including IDE, database server, GIT, Continuous Integration, unit-testing tool, and defect management tools. Knowledge Strong Knowledge of Data Engineering concepts (Data pipelines creation, Data Warehousing, Data Marts/Cubes, Data Reconciliation and Audit, Data Management). Strong working knowledge of Snowflake, including warehouse management, Snowflake SQL, and data sharing techniques. Experience building pipelines that source from or deliver data into Snowflake in combination with tools like ADF and Databricks. Working Knowledge of Dev-Ops processes (CI/CD), Git/Jenkins version control tool, Master Data Management (MDM) and Data Quality tools. Strong Experience in ETL/ELT development, QA and operation/support process (RCA of production issues, Code/Data Fix Strategy, Monitoring and maintenance). Hands on experience in Databases like (Azure SQL DB, MySQL/, Cosmos DB etc.), File system (Blob Storage), Python/Unix shell Scripting. ADF, Databricks and Azure certification is a plus. Technologies we use: Databricks, Azure SQL DW/Synapse, Azure Tabular, Azure Data Factory, Azure Functions, Azure Containers, Docker, DevOps, Python, PySpark, Scripting (Powershell, Bash), Git, Terraform, Power BI, Snowflake #LI-DS1
