Capgemini, a diverse global collective of thinkers and entrepreneurs, seeks a Senior Data Engineer to reimagine technological possibilities. Discover the future you want with Capgemini.
In this role you can expect to have the responsibilities: Develop solutions using Azure Data Factory and Databricks. Implement CI/CD pipelines with DevOps. Work extensively with Databricks notebooks using SQL, PySpark, and Python. Utilize Azure Data Lake and cloud storage accounts. Handle Delta lakehouse and delta live tables. Execute various data ingestion methods, including API, file-based, and database ingestion. Integrate Git for ADF pipeline versioning and collaboration. Manage source control in DevOps using Git, including branching, merging, and pull requests. This role comes with the following benefits: Access to premier learning platforms and certifications. Minimum of 40 hours of training per year. Recognized as one of the World's Most Ethical Companies. Commitment to diversity and inclusion. Support for disabilities and neurodivergent candidates. Commitment to carbon neutrality by 2025. This role requires you to have: Experience with Azure Data Factory and Databricks. Proficiency in CI/CD pipelines using DevOps. Knowledge of Databricks notebooks and Python. Skilled in Azure Data Lake and cloud storage. Understanding of Delta lakehouse and delta live tables. API-based, file-based, and database data ingestion methods. Git integration for ADF pipeline versioning. Experienced in SQL queries and concepts. Development of Oracle procedures and packages. Data modelling and building materialised views. Familiarity with VI editor and Linux commands. Shell scripting experience. You would benefit from having: Proficiency in PySpark. Capgemini Australia adheres to ISO9001, ISO27001, and ISO14001 standards, ensuring the delivery of secure and compliant solutions.
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