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The Data Engineer is expected to be in charge of the whole lifecycle of the datasets, including updates, backups, synchronization, and policy access. Managing the lifecycle (from data collection to archive) of ML/DL datasets and ensure their usability for the client’s data scientists. Design, build and integrate data from various sources. Design ETL pipelines with scripted components. Optimize data workflows, choosing the most cost-efficient approach. Automate the management of recurrent task in the pipeline. Perform feasibility studies/analysis with a critical point of view. Support and maintain (troubleshoot issues with data and applications). Develop technical documentation for applications, including diagrams and manuals. Work on many different software challenges always ensuring a combination of simplicity and maintainability within the code. Contribute to architectural designs of large complexity and size, potentially involving several distinct software components. Working closely with data scientists and a variety of end-users (across different cultures) to ensure technical compatibility and user satisfaction. Work as a member of a team, encouraging team building, motivation and cultivate an effective team
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