Senior Data Engineer (Snowflake)

Capgemini is an AI-powered global business and technology transformation partner with nearly 60 years of heritage, employing 420,000 team members in over 50 countries. The Insights & Data organization delivers state-of-the-art data solutions across industries, specializing in Cloud and Big Data engineering using cloud services across AWS, Azure, and GCP, leveraging ETL tools, programming languages such as Python, Scala, and Java, and DevOps best practices.

• Experience with Big Data or Cloud projects involving large and/or unstructured datasets.
• Strong understanding of Snowflake’s pricing model and cost optimization strategies.
• Practical skills in designing and implementing data transformation pipelines using native Snowflake features or partner services.
• Familiarity with Snowflake’s security model.
• Knowledge of at least one public cloud platform including Storage, Compute/Serverless, Networking, or DevOps.
• Working knowledge of SQL and at least one programming language: Python, Scala, Java, or Bash.
• Very good command of English.

• Design, develop, and maintain Snowflake data pipelines supporting key business functions.
• Collaborate with cross-functional teams to gather data requirements and build scalable cloud solutions.
• Optimize data models and schemas for performance, efficiency, and cost-effectiveness in Snowflake.
• Ensure data quality, integrity, and security throughout the data lifecycle.
• Implement monitoring and alerting mechanisms to proactively identify and resolve issues.
• Plan and execute migrations from on-premises data warehouses to Snowflake.
• Develop solutions involving AI, Machine Learning, and Generative AI aligned with business needs.
• Stay current with Snowflake best practices and emerging technologies to drive continuous improvement.

Capgemini is committed to diversity and inclusion, ensuring fairness in all employment practices by evaluating individuals based on qualifications and performance rather than personal characteristics.