Capgemini is looking to unlock the value of technology and build a more sustainable, more inclusive world for the world's leading organizations
Requirements
- 8- 10+ years of experience in data engineering, cloud platforms, and big data technologies.
- Strong proficiency in Azure services: Data Factory, Synapse, Data Lake, Azure SQL, Cosmos DB.
- Experience with Python, Spark, SQL, and distributed data processing.
- Familiarity with AI/ML workflows and tools such as Azure ML, MLflow, and OpenAI APIs.
- Understanding of data governance, security, and compliance in cloud environments.
Responsibilities
- Design, build, and maintain scalable ETL/ELT pipelines using Azure Data Factory, Synapse Pipelines, and Databricks.
- Ingest, transform, and curate structured and unstructured data from diverse sources for AI/ML consumption.
- Optimize data workflows for performance, reliability, and cost-efficiency.
- Enable data access and preparation for Azure AI services including Azure Machine Learning, Azure OpenAI, and Cognitive Services.
- Collaborate with data scientists and ML engineers to operationalize AI models using MLOps and GenAIOps practices.
- Support RAG (Retrieval-Augmented Generation) and other GenAI patterns through data engineering best practices.
- Implement CI/CD pipelines for data workflows using Azure DevOps or GitHub Actions.
Other
- 8- 10+ years of experience
- Paid time off and paid holidays
- Paid parental leave
- Family building benefits like adoption assistance, surrogacy, and cryopreservation
- Social well-being benefits like subsidized back-up child/elder care and tutoring
