Internship - Data Engineering & Analytics
Paris, France
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- Pay not listed
- Work setting
- Not stated
- Employment
Internship — employment source
Employment type in the employer’s posting: INTERN
From the employer’s posting
What you’ll work on
Full postingDesign and build an ETL pipeline in Databricks to ingest and clean claims data
Collect and inventory nat cat claims data from Excel, CSV and JSON sources
Apply data quality checks and validation rules to keep the data accurate
Build a user-friendly data upload interface in Databricks for non-technical users
Build an interactive dashboard on the cleaned data layer
From the employer’s posting
Designing and implementing an ETL (Extract, Transform, Load) pipeline in Databricks to automate data ingestion, cleaning, and standardization
Collecting, cleaning, and inventorying nat cat claims data stored across various sources and formats (Excel, CSV, JSON, etc.)
Applying data quality checks and validation rules to ensure accuracy and consistency of the data
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.
Building an interactive dashboard connected to the cleaned Databricks data layer
Tools in this posting
- Python
- R
- SQL
- Databricks
- Delta Lake
- Excel
- pandas
- PySpark
Source — Tool mentions in context
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) YOUR PROFILE - Who You Are Education 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 We encourage you to apply even if you do not fully meet all the qualifications listed.
YOUR ROLE AND RESPONSIBILITIES What You’ll Do Building a centralized and reliable data pipeline 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.
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- Live
- First seen by us
- Oct 8, 2026 · 21 days ago
- Recorded sightings
- 119
- Last seen by us
- Oct 30, 2026
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Paris, France
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