Data Engineer Job in Capgemini

As a Cloud Data Engineer at Capgemini Invent, you will be responsible for designing, developing, and maintaining scalable ETL/ELT pipelines and managing cloud data platforms. You will work with modern cloud technologies to process and analyze structured, semi-structured, and unstructured data, optimizing data lakes, warehouses, and cloud utility functions. Your expertise will help deliver robust cloud-based data solutions that power business decision-making.

Key Responsibilities:

• ETL/ELT Pipeline Development: Design and develop scalable ETL/ELT pipelines to process a variety of data types (structured, semi-structured, unstructured) in cloud environments.

• Cloud Data Solutions: Build, optimize, and maintain cloud storage solutions, data lakes, and data warehousing solutions using platforms such as Snowflake, BigQuery, AWS Redshift, ADLS, and S3.

• Cloud Utility Functions: Develop cloud utility functions leveraging services like AWS Lambda, AWS Step Functions, Cloud Run, Cloud Functions, and Azure Functions.

• Cloud Data Integration: Use cloud-native data integration tools (such as Azure Databricks, Azure Data Factory, AWS Glue, AWS EMR, Dataflow, Dataproc) to transform and analyze data from multiple sources.

• Cloud Infrastructure Management: Manage and optimize cloud compute services, data storage, load balancing, and ensure efficient cloud identity management, authentication, and authorization processes.

• Data Processing and Analysis: Lead initiatives to clean, transform, and process data, ensuring it is ready for analytics and reporting. Develop processes for continuous data integration and transformation.

Your Profile:

• Experience: 8-10 years of IT experience, with at least 5 years of hands-on experience in cloud data engineering, focusing on ETL/ELT, data pipelines, and data storage solutions.

• Cloud Expertise: Proven experience working with cloud platforms such as AWS, Azure, or GCP. Familiarity with data storage, cloud data warehouses, and data lakes like Snowflake, BigQuery, AWS Redshift, ADLS, and S3.

• Cloud Utility Functions: Proficient in developing cloud utility functions using services like AWS Lambda, AWS Step Functions, Cloud Run, Cloud Functions, and Azure Functions.

• Data Integration Experience: Expertise with cloud-based data integration tools, such as Azure Databricks, Azure Data Factory, AWS Glue, AWS EMR, Dataflow, Dataproc, for working with structured, semi-structured, and unstructured data.

• Cloud Infrastructure Knowledge: Strong understanding of cloud compute services, load balancing, and cloud identity management practices (authentication and authorization).

What You Will Love About Working Here:

• Flexible Work Arrangements: Enjoy the ability to work remotely or with flexible hours, ensuring you can maintain a healthy work-life balance.

• Career Growth: Capgemini Invent is committed to your professional growth. We offer a range of career development programs to help you explore a world of opportunities and reach your full potential.

• Learning and Development: Take advantage of the opportunity to acquire valuable certifications in the latest technologies, including Generative AI.