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# Stage - Data Engineering & Analytics

- **Company:** AXA
- **Location:** Paris, France (Remote available)
- **Salary:** €65,000.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Excel, Computer Programming, Data Dictionary, Information Engineering, Extract Transform Load (ETL), Data Visualization, JSON, Python (Programming Language), Standard Sql, DataOps, Systems Integration, Data Ingestion, Data Layers, Pandas, Data Lakes, Pyspark, Information Technology, Data Analytics, Software Version Control, Data Pipelines, Databricks
- **Published:** October 10, 2026
- **Apply:** https://www.studentjob.fr/offre/8911071-stage-data-engineering-analytics/reaction/nouveaute

## About the Role

* Engineering or Master's degree in a relevant field (Computer Science, Data Engineering, Applied Mathematics, Statistics, or equivalent)

Technical & Professional Skills

 * Programming skills in Python/R (pandas, PySpark) and/or SQL
 * Experience or strong interest in Databricks (notebooks, Delta Lake, workflows)
 * Familiarity with ETL pipeline design and data quality concept
 * French and Business English - fluent (spoken and written)

Interpersonal skills

 * Autonomous and resourceful
 * Rigorous and detail-oriented
 * Strong communication skills
 * Curious and eager to learn about the insurance industry
 * Motivated by working in an international and dynamic environment

## Description

* Collecting, cleaning, and inventorying nat cat claims data stored across various sources and formats (Excel, CSV, JSON, etc.)
 * Designing and implementing an ETL (Extract, Transform, Load) pipeline in Databricks to automate data ingestion, cleaning, and standardization
 * Applying data quality checks and validation rules to ensure accuracy and consistency of the data

Developing a user-friendly data loading/extraction interface

 * Creating an intuitive interface within Databricks (e.g., using Databricks Widgets or a notebook-based UI) allowing non-technical users to load/submit data with ease.
 * Implementing clear error messages and guided workflows to support data contributors across teams.

Enabling data visualization and self-service analytics

 * Building an interactive dashboard connected to the cleaned Databricks data layer, providing meaningful insights on the claims data
 * Integrating a data download feature, allowing authorized users to export clean, structured datasets directly from the platform

Documenting and maintaining the solution

 * Producing clear technical documentation covering the pipeline architecture, data dictionaries, and user guides
 * Following data engineering best practices (version control, modular code, reproducibility)