Data Analytics Engineer

As an FBS Associate Analytics Engineer at Capgemini, you will be part of a dynamic team dedicated to delivering cutting-edge analytics solutions for clients. Your role will involve working with different business teams to help with Data Engineering, Architecture, and Solutioning. You will be responsible for building complex data products and data assets to support the organization's D&A needs. Your strong technical skills in Python, SQL, PySpark, and cloud technologies will be crucial in solving business challenges related to data and data products. Key Responsibilities: - Collaborate with different business teams and IT to ensure the required data is available to support their needs - Become a subject matter expert on the different source systems and data products, assisting business users with their data needs - Support existing data assets and products by refreshing the data - Work on Data Engineering, Data Quality & Data Management, ETL, Data Warehousing & Data Lake - Utilize Python, SQL, Snowflake, PySpark, and AWS (Lambda, EMR, Step Function) in your day-to-day tasks Qualifications Required: - Proficiency in Python, SQL, PySpark, and cloud technologies - Experience with Data Engineering, Data Quality, ETL processes, Data Warehousing & Data Lake - Knowledge of AWS services such as Lambda, EMR, and Step Function Capgemini is a global business and technology transformation partner with a strong heritage of over 55 years. The company is committed to helping organizations accelerate their transition to a digital and sustainable world, creating tangible impact for enterprises and society. With a diverse team of 340,000 members in more than 50 countries, Capgemini is trusted by clients to unlock the value of technology across various business needs. The company offers end-to-end services and solutions, leveraging expertise in AI, cloud, data, and industry-specific knowledge to drive innovation and transformation. As an FBS Associate Analytics Engineer at Capgemini, you will be part of a dynamic team dedicated to delivering cutting-edge analytics solutions for clients. Your role will involve working with different business teams to help with Data Engineering, Architecture, and Solutioning. You will be responsible for building complex data products and data assets to support the organization's D&A needs. Your strong technical skills in Python, SQL, PySpark, and cloud technologies will be crucial in solving business challenges related to data and data products. Key Responsibilities: - Collaborate with different business teams and IT to ensure the required data is available to support their needs - Become a subject matter expert on the different source systems and data products, assisting business users with their data needs - Support existing data assets and products by refreshing the data - Work on Data Engineering, Data Quality & Data Management, ETL, Data Warehousing & Data Lake - Utilize Python, SQL, Snowflake, PySpark, and AWS (Lambda, EMR, Step Function) in your day-to-day tasks Qualifications Required: - Proficiency in Python, SQL, PySpark, and cloud technologies - Experience with Data Engineering, Data Quality, ETL processes, Data Warehousing & Data Lake - Knowledge of AWS services such as Lambda, EMR, and Step Function Capgemini is a global business and technology transformation partner with a strong heritage of over 55 years. The company is committed to helping organizations accelerate their transition to a digital and sustainable world, creating tangible impact for enterprises and society. With a diverse team of 340,000 members in more than 50 countries, Capgemini is trusted by clients to unlock the value of technology across various business needs. The company offers end-to-end services and solutions, leveraging expertise in AI, cloud, data, and industry-specific knowledge to drive innovation and transformation.