Junior Data Engineer

You will be a key member of a growing and passionate group focused on collaborating across business and technology resources to drive forward key programs and projects building enterprise capabilities across Advance Auto Parts. Responsibilities: - Help in the migration and modernization of data platforms, moving applications and pipelines to Google Cloud-based solutions. - Ensure data security and governance, enforcing compliance with industry standards and regulations. - Help in managing and scaling data pipelines from internal and external data sources to support new product launches and ensure high data quality. - Help in developing automation and monitoring frameworks to capture key metrics and operational KPIs for pipeline performance. - Collaborate with internal teams, including data science and product teams, to drive solutioning and proof-of-concept (PoC) discussions. - Help in developing and optimizing procedures to transition data into production. - Create and maintain technical documentation for sharing knowledge. - Help in developing reusable packages and libraries to enhance development efficiency. - Help in developing real-time and batch data processing solutions, integrating structured and unstructured data sources. Required Qualification: - 1-2 years of experience in Data Engineering and Application development. - Graduate degree in Computer Science or a related field of study. - Experience with programming languages such as Python, Java & DS&Algo, Spark, and Scala. - Expertise in Python and Spark is a must. - Exposure to AWS and Cloud technologies. - Experience in data platform engineering, with a focus on cloud transformation and modernization. - Hands-on experience building large, scaled data pipelines in cloud environments and handling data in PBs. - Experience with CI/CD pipeline management in GCP DevOps. - Understanding of data governance, security, and compliance best practices. - Experience working in an Agile development environment. - Prior experience in migrating applications from legacy platforms to the cloud. - Knowledge of Terraform or Infrastructure-as-Code (IaC) for cloud resource management. - Familiarity with Kafka, Event Hubs, or other real-time data streaming solutions. - Experience with legacy RDBMS (Oracle, DB2, Teradata) & DataStage/Talend. - Background supporting data science models in production. You will be a key member of a growing and passionate group focused on collaborating across business and technology resources to drive forward key programs and projects building enterprise capabilities across Advance Auto Parts. Responsibilities: - Help in the migration and modernization of data platforms, moving applications and pipelines to Google Cloud-based solutions. - Ensure data security and governance, enforcing compliance with industry standards and regulations. - Help in managing and scaling data pipelines from internal and external data sources to support new product launches and ensure high data quality. - Help in developing automation and monitoring frameworks to capture key metrics and operational KPIs for pipeline performance. - Collaborate with internal teams, including data science and product teams, to drive solutioning and proof-of-concept (PoC) discussions. - Help in developing and optimizing procedures to transition data into production. - Create and maintain technical documentation for sharing knowledge. - Help in developing reusable packages and libraries to enhance development efficiency. - Help in developing real-time and batch data processing solutions, integrating structured and unstructured data sources. Required Qualification: - 1-2 years of experience in Data Engineering and Application development. - Graduate degree in Computer Science or a related field of study. - Experience with programming languages such as Python, Java & DS&Algo, Spark, and Scala. - Expertise in Python and Spark is a must. - Exposure to AWS and Cloud technologies. - Experience in data platform engineering, with a focus on cloud transformation and modernization. - Hands-on experience building large, scaled data pipelines in cloud environments and handling data in PBs. - Experience with CI/CD pipeline management in GCP DevOps. - Understanding of data governance, security, and compliance best practices. - Experience working in an Agile development environment. - Prior experience in migrating applications from legacy platforms to the cloud. - Knowledge of Terraform or Infrastructure-as-Code (IaC) for cloud resource management. - Familiarity with Kafka, Event Hubs, or other real-time data streaming solutions. - Experience with legacy RDBMS (Oracle, DB2, Teradata) & DataStage/Talend. - Background supporting data science models in production.