[Hiring] Senior Data Engineer @Capgemini

Role Description

Design, build, and maintain data pipelines and ETL processes using Databricks and Apache Spark.

• Optimize data workflows for performance, scalability, and cost efficiency.
• Implement data Lakehouse architecture and manage data ingestion from multiple sources.
• Collaborate with data scientists and analysts to enable advanced analytics and machine learning workloads.
• Ensure data quality, governance, and security across all data assets.
• Monitor and troubleshoot Databricks clusters, jobs, and workflows.
• Integrate Databricks with cloud services (AWS, Azure, or GCP) and other enterprise systems.
• Document processes, standards, and best practices for data engineering.

Qualifications

• Experience with Delta Lake and Lakehouse architecture.
• Knowledge of Azure Data Factory (ADF) for orchestration.
• Exposure to CI/CD pipelines for data engineering.
• Experience with SQL and Spark SQL.
• Azure certifications related to data engineering.

Benefits

• Encouragement of flexibility in how, when, and where work is done for better work-life balance.
• Opportunities to achieve valuable change and create new connections and technologies.
• Support for deepening knowledge and learning new skills while performing job duties.

Company Description

Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided every day by its purpose of unleashing human energy through technology for an inclusive and sustainable future.

• Responsible and diverse organization of over 300,000 team members in nearly 50 countries.
• Strong 50-year heritage and deep industry expertise.
• Trusted by clients to address the entire breadth of their business needs, from strategy and design to operations.