Data Engineer - Freelance (H/F)

France | Sept. 24, 2026

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Company: Collective.work

Country: France

Type: Onsite

Employment: Full-time

Description: CONTEXT

A company specializing in distribution is embarking on a profound transformation of its model, where each product designed, sold or repaired is traced, measured and optimized to reduce its footprint on the planet.

Controlling the environmental impact from the carbon footprint of each product sold to the performance of repair workshops, including the complete life cycle of second-life items, constitutes a major strategic lever in achieving this ambition. The role of the team is to build and make all Sustainability, Circular Economy and Workshop data reliable.

The team is currently made up of:

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   4 Product Managers

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   7 Data Engineers

MISSIONS

As a Data Engineer within the Planet team, you will work on 2 products managed by the team:

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   Service: extend the life of products by structuring data from all circular flows

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   Sustainability: measure and reduce the carbon footprint of each product sold, from its design (eco-design, preferred materials) to its impact on the shelf, to manage the company's environmental trajectory

Your responsibilities:

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  Implement solutions, based on the functional rules established by the Product Manager / Data Owner

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   Document the quality rules described in Collibra beforehand to validate the datasets

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   Start from generic templates to build scalable structured data pipelines

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   Transform the legacy stack to the new stack recommended by the Data Platform teams

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   Answer questions from users as well as the data visualization team on the data made available

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   Be able to intervene on all of the team's flows

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   Document the implemented flows

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   Contribute to the improvement of good development practices within the team (Mob programming, Test Driven Development, etc.)
(DBT, PySpark)
Advanced AWS S3 Advanced Python Advanced PySpark Advanced Databricks Advanced SQL Language Confirmed

1. Experience on Amazon Web Services (AWS) Big Data environment including using components such as S3, CodeArtefact, ECR and optimizing their performance
2. Experience in implementing data pipelines with DBT and PySpark
3. Skills in setting up scheduling via Airflow
4. Knowledge of Databricks
5. Development in Python
6. Knowledge of data modeling
7. Advanced mastery of Spark, AWS S3, Python, PySpark and DATABRICKS
8. Confirmed level in SQL language

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