Data Preparation Analyst / Data Preparation Senior Analyst

Role Overview: At the Circle K Business Centre in India, you will be part of a dynamic team using data analytics to drive decisions and strengthen Circle K's global capabilities. Your role will involve partnering with various departments such as Global Marketing, Merchandising, Global Technology, and Business Units to drive data engineering activities for advanced analytics projects. You will play a crucial role in interpreting business questions, working with large datasets, and complying with data governance frameworks to deliver effective results. Key Responsibilities: - Prototype, build, deploy, and manage data engineering pipelines to move data across platforms and provide intuitive analytics to stakeholders - Define data architecture, explore trade-offs, and build data pipelines for on-premise and cloud-based Business Intelligence/AI/ML systems - Build logical and physical data models for OLTP and OLAP solutions - Maintain ETL playbook documentation, resolve ETL-related issues, and contribute to shared data engineering tooling & standards - Improve data quality by using tools to automatically detect issues and maintain data standards and best practices across the Engineering team - Work with data science and visualization professionals to productize data science algorithms into analytical software Qualifications Required: - Bachelors Degree in Computer Science or related technical field - 2-4 years of relevant experience for Analyst, 4-6 years for Sr. Analyst in a quantitative/applied analytics role - Knowledge of Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics, etc.) - Familiarity with Enterprise reporting systems, relational/non-relational database management systems, and Data Engineering tools - Proficiency in Big data technologies (Hadoop, Spark, Kafka, Presto) and Cloud computing services (Azure/AWS/GCP) for data engineering and ML Ops - Strong ability to deliver, business acumen, and interpersonal communication skills - Organized, dependable, able to multitask, display initiative, and work independently in a fast-paced environment (Note: Additional details about the company were not provided in the job description) Role Overview: At the Circle K Business Centre in India, you will be part of a dynamic team using data analytics to drive decisions and strengthen Circle K's global capabilities. Your role will involve partnering with various departments such as Global Marketing, Merchandising, Global Technology, and Business Units to drive data engineering activities for advanced analytics projects. You will play a crucial role in interpreting business questions, working with large datasets, and complying with data governance frameworks to deliver effective results. Key Responsibilities: - Prototype, build, deploy, and manage data engineering pipelines to move data across platforms and provide intuitive analytics to stakeholders - Define data architecture, explore trade-offs, and build data pipelines for on-premise and cloud-based Business Intelligence/AI/ML systems - Build logical and physical data models for OLTP and OLAP solutions - Maintain ETL playbook documentation, resolve ETL-related issues, and contribute to shared data engineering tooling & standards - Improve data quality by using tools to automatically detect issues and maintain data standards and best practices across the Engineering team - Work with data science and visualization professionals to productize data science algorithms into analytical software Qualifications Required: - Bachelors Degree in Computer Science or related technical field - 2-4 years of relevant experience for Analyst, 4-6 years for Sr. Analyst in a quantitative/applied analytics role - Knowledge of Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics, etc.) - Familiarity with Enterprise reporting systems, relational/non-relational database management systems, and Data Engineering tools - Proficiency in Big data technologies (Hadoop, Spark, Kafka, Presto) and Cloud computing services (Azure/AWS/GCP) for data engineering and ML Ops - Strong ability to deliver, business acumen, and interpersonal communication skills - Organized, dependable, able to multitask, display initiative, and work independently in a fast-paced environment (Note: Additional details about the company were not provided in the job description)