Senior Data Platform Engineer (DevOps)

Capgemini is a global business transformation partner with over 410,000 team members, specializing in AI, cloud, and data to help enterprises build intelligent, sustainable futures. The Insights & Data practice at Capgemini merges cloud technologies, big data processing, automation, MLOps, and generative AI to create scalable data ecosystems and innovative data solutions.

• Practical experience building data platforms using one or more cloud providers: AWS, Azure, or GCP.
• Strong understanding of large-scale data processing including Spark, Hive, Snowflake, Delta Lake or similar.
• Excellent SQL skills and experience with relational and/or NoSQL databases.
• Programming skills in Python or Scala.
• Experience with CI/CD tools such as Azure DevOps, GitHub Actions, GitLab CI, Jenkins.
• Hands-on experience with Docker and Kubernetes.
• Knowledge of DataOps principles, data testing, and monitoring.
• Good understanding of data security, encryption, and identity/access management.

Nice to have:

• Familiarity with cloud AI/ML services or generative AI tools.

• Design and develop scalable cloud-based Data Platforms (including AWS, Azure, GCP).
• Build, optimize, and maintain data pipelines for batch and streaming workloads.
• Integrate with diverse data sources and expose data through APIs, semantic layers, and data warehouses.
• Work with orchestration tools (e.g., Dataflow, Data Pipeline, ADF, MWAA, Cloud Composer).
• Work with compute and processing services (e.g., Databricks, EMR, Glue, DataProc, Snowflake).
• Work with event-driven services (e.g., EventBridge, Pub/Sub, Event Hub).
• Design, develop, and optimize data models and multi-layered processing architectures (bronze/silver/gold).
• Ensure efficient performance and optimization of SQL and NoSQL solutions.
• Collaborate with Data Scientists and engineering teams to operationalize ML models.
• Document data architectures, workflows, and technical processes.
• Ensure security, compliance, and robust data governance across the platform.
• Participate in architectural discussions and contribute to technology recommendations.