Everience is an international consulting group delivering AI-augmented digital services. The Senior Data Engineer will play a key role in managing, integrating, and optimizing data across upstream and downstream activities, with a focus on data used for forecasting. You will ensure data quality, consistency, and accessibility across multiple sources, enabling efficient use by business stakeholders, data analysts, and data scientists. You will contribute to data governance initiatives, support architectural decisions, and implement best practices in data management. Responsibilities include capturing, integrating, and processing structured and unstructured data from internal and external sources; designing, developing, and maintaining robust ETL/ELT pipelines; standardizing, qualifying, and documenting data to ensure consistency and usability; mapping and maintaining data lineage and data source documentation; monitoring and improving data quality through validation, testing, and cleansing processes; identifying and eliminating duplicates, incomplete, or inconsistent data; ensuring the quality and reliability of data entering the Data Lake; contributing to the creation and maintenance of data repositories; promoting and implementing best practices in data governance and data management. Development and Architecture responsibilities include developing solutions within the enterprise data framework, writing technical specifications and design documentation, developing and executing unit tests to ensure solution reliability, participating in technical and architectural discussi

Everience is an international consulting group delivering AI-augmented digital services. The Senior Data Engineer will play a key role in managing, integrating, and optimizing data across upstream and downstream activities, with a focus on data used for forecasting. You will ensure data quality, consistency, and accessibility across multiple sources, enabling efficient use by business stakeholders, data analysts, and data scientists. You will contribute to data governance initiatives, support architectural decisions, and implement best practices in data management. Responsibilities include capturing, integrating, and processing structured and unstructured data from internal and external sources; designing, developing, and maintaining robust ETL/ELT pipelines; standardizing, qualifying, and documenting data to ensure consistency and usability; mapping and maintaining data lineage and data source documentation; monitoring and improving data quality through validation, testing, and cleansing processes; identifying and eliminating duplicates, incomplete, or inconsistent data; ensuring the quality and reliability of data entering the Data Lake; contributing to the creation and maintenance of data repositories; promoting and implementing best practices in data governance and data management. Development and Architecture responsibilities include developing solutions within the enterprise data framework, writing technical specifications and design documentation, developing and executing unit tests to ensure solution reliability, participating in technical and architectural discussi