Join Capgemini Invent as a Data Engineer and be a part of a team driving inventive transformation for clients. We combine strategic, creative, and scientific expertise to deliver cutting-edge solutions informed by data and powered by technology. This role is key to developing and maintaining scalable data pipelines, ensuring data accuracy, and collaborating with cross-functional teams to meet client challenges.

Your primary focus will be designing, developing, and maintaining robust data pipelines using Snowflake, writing efficient Python and PySpark code, and optimizing SQL queries. You will implement data ingestion strategies with Snowpipe and COPY commands, extract and load data from diverse sources, and configure role-based access within Snowflake. Creating DBT models, integrating data quality rules, and implementing monitoring systems are also critical aspects of this role. You'll collaborate with stakeholders to translate requirements into technical solutions, ensuring data quality, governance, and security across all layers.

We are seeking candidates proficient in Python, PySpark, and SQL, with strong query optimization skills. Experience with Snowflake and cloud platforms like AWS, Azure, or GCP is essential. Familiarity with data warehousing concepts, ETL processes, and big data tools such as Hadoop, Spark, and Kafka is required. Experience with relational databases (SQL Server, MySQL, PostgreSQL, Oracle) and NoSQL databases (Hadoop, Cassandra, MongoDB) is also expected. Excellent problem-solving abilities and a knack for sustainable, reusable development are highly valued.