We are looking for a Python & PySpark Data Developer to join our partner team in a hybrid setup (2-3 days per week on-site), bringing strong data engineering expertise and hands-on experience in building and maintaining ETL pipelines. 

What You Will Do:

• Identify and select relevant data sources to be ingested into the data lake based on business and analytical requirements.
• Design and manage the structure and organization of data within the data lake to ensure accessibility, scalability, and optimal performance.
• Develop and maintain ETL pipelines using PySpark for data cleaning, transformation, and integration from multiple sources.
• Configure ETL components such as data formatting, deduplication, volumetric analysis, and enrichment, ensuring all processes are thoroughly documented.
• Contribute to defining and designing new use cases by identifying relevant data, transforming it, and preparing it for analysis.
• Develop and maintain interactive dashboards that visualize key metrics and insights derived from processed data.
• Monitor and troubleshoot data workflows to maintain reliability, scalability, and accuracy in production environments.
• Document pipeline logic, data sources, transformation rules, and operational flows for transparency and maintainability.

Technical Skills:

• Proficiency in Python and PySpark for data processing and pipeline development.

• Strong SQL skills and experience working with relational databases.

• Familiarity with data warehousing platforms (e.g., Cloudera).

• Understanding of data modeling, data lakes, and data governance principles.

• Experience with dashboarding tools (Power BI, Tableau, etc.) is a plus.

Preferred Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science or

  a related field.

• Fluent English is required; French is a plus but not mandatory.

• Knowledge of business intelligence and data storytelling principles.