Data Engineer (Snowflake)

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Job Description

Your Profile

• Build and optimize modern data pipelines using Snowflake, SQL, Python, dbt, and Matillion, ensuring reliable and scalable data solutions that support enterprise reporting, analytics, and AI initiatives.

• Own end-to-end data integration processes, including developing ELT/ETL workflows, troubleshooting data issues, improving data quality, and maintaining production-ready data products.

• Drive Snowflake platform performance and efficiency, identifying opportunities to improve query execution, warehouse utilization, scalability, and cost optimization across the data ecosystem.

• Work closely with cross-functional teams including Data Architects, Analytics teams, Platform Engineers, and business stakeholders to translate requirements into robust and reusable data solutions.

• Participate in production support and continuous improvement efforts, performing root cause analysis, automating manual processes, enhancing monitoring capabilities, and contributing to CI/CD and engineering best practices.

Your Role

• 4+ years of total Data Engineering experience with 2+ years of hands-on Snowflake experience in enterprise environments. Including data warehouse design, performance tuning, workload optimization, cost management, and building scalable enterprise data solutions.

• Advanced SQL and query optimization skills, with the ability to design complex data transformations, troubleshoot performance bottlenecks, and optimize large-scale datasets efficiently.

• Python and data engineering development experience, building reusable frameworks, automation solutions, and production-grade data pipelines.

• Expertise with DBT, including designing, developing, testing, and maintaining robust ELT/ETL processes following software engineering best practices.

• Deep understanding of data modeling, data warehousing, and production support, combined with experience using GitHub, CI/CD pipelines, root cause analysis, and data quality monitoring to deliver reliable enterprise data products.

• Fluent English level

What you'll love

• Work on meaningful projects that use technology to solve real-world challenges.

• Be part of a company that values sustainability, inclusion, and digital equity.