Lead Data Engineer

Job Description Job Description Alimentation Couche-Tard Inc., (ACT) is a global Fortune 200 company. A leader in the convenience store and fuel space with over 16,700 stores in 31 countries, serving more than 9 million customers each day. At Circle K, we are building a best-in-class global data engineering practice to support intelligent business decision-making and drive value across our retail ecosystem. As we scale our engineering capabilities, we're seeking a Lead Data Engineer to serve as both a technical leader and people coach for our India-based Data Enablement pod. This role will oversee the design, delivery, and maintenance of critical cross-functional datasets and reusable data assets while also managing a group of talented engineers in India. This position plays a dual role: contributing hands-on to engineering execution while mentoring and developing engineers in their technical careers. About The Role The ideal candidate combines deep technical acumen, stakeholder awareness, and a people-first leadership mindset. You'll collaborate with global tech leads, managers, platform teams, and business analysts to build trusted, performant data pipelines that serve use cases beyond traditional data domains. Responsibilities - Design, develop, and maintain scalable pipelines across ADF, Databricks, Snowflake, and related platforms - Lead the technical execution of non-domain specific initiatives (e.g. reusable dimensions, TLOG standardization, enablement pipelines) - Architect data models and re-usable layers consumed by multiple downstream pods - Guide platform-wide patterns like parameterization, CI/CD pipelines, pipeline recovery, and auditability frameworks - Mentoring and coaching team - Partner with product and platform leaders to ensure engineering consistency and delivery excellence - Act as an L3 escalation point for operational data issues impacting foundational pipelines - Own engineering best practices, sprint planning, and quality across the Enablement pod - Contribute to platform discussions and architectural decisions across regions Job Requirements Education - Bachelor's or master's degree in computer science, Engineering, or related field Relevant Experience - 8-10 years of data engineering experience with strong hands-on delivery using ADF, SQL, Python, Databricks, and Spark - Experience designing data pipelines, warehouse models, and processing frameworks using Snowflake or Azure Synapse Knowledge And Preferred Skills - Proficient with CI/CD tools (Azure DevOps, GitHub) and observability practices. - Solid grasp of data governance, metadata tagging, and role-based access control. - Proven ability to mentor and grow engineers in a matrixed or global environment. - Strong verbal and written communication skills, with the ability to operate cross-functionally. - Certifications in Azure, Databricks, or Snowflake are a plus. - Strong Knowledge of Data Engineering concepts (Data pipelines creation, Data Warehousing, Data Marts/Cubes, Data Reconciliation and Audit, Data Management). - 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, Snowflake, 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, Snowflake, Azure Tabular, Azure Data Factory, Azure Functions, Azure Containers, Docker, DevOps, Python, PySpark, Scripting (Powershell, Bash), Git, Terraform, Power BI