The role involves designing, developing, industrializing, and maintaining reliable and high-performance data pipelines. The professional will work on international projects across various sectors such as finance, industry, retail, mobility, and energy. Responsibilities include implementing advanced data transformations and ensuring the quality and scalability of data processing. The position requires active participation in DataOps practices, including automation, testing, and versioning. Additionally, the role involves acting as a technical reference for development teams and contributing to architectural improvements and internal documentation.

The role requires a minimum of three to five years of experience in data engineering, specifically with demonstrated expertise in setting up batch and streaming dataflows using Databricks. Candidates must possess advanced proficiency in PySpark or Scala and have experience with at least one major cloud provider, such as Azure, AWS, or GCP. Strong knowledge of CI/CD tools and practices is necessary for the position. While not explicitly stated as a mandatory degree requirement, the role emphasizes the importance of technical certifications, particularly those related to Databricks.