Databricks Engineer

Main mission

We are looking for a Data Enginee r with strong expertise in Databrick s and Pytho n to design, build, and optimize scalable data solutions across modern cloud platforms. In this role, you will develop secure, reliable, and high-performance data pipelines that transform data from multiple sources into trusted datasets for analytics, reporting, and AI initiatives. Working closely with Data Analysts, Architects, and Product Teams, you will ensure data is accessible, scalable, and aligned with business needs.

Key responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Databric ks and Python
• Build data ingestion, transformation, and orchestration workflows from structured and unstructured data sources
• Develop cloud-native data solutions using Azure and/or AWS .
• Ensure data pipelines are secure, scalable, reliable, and optimized for performance.
• Implement monitoring, alerting, logging, and operational support processes
• Apply data quality, validation, and consistency controls across data pipelines
• Contribute to data modeling and transformation activities to support analytics and business applications.
• Produce technical documentation, including architecture diagrams and data flow documentation.Collaborate with Data Analysts, Architects, and Product Teams to deliver end-to-end data solutions.
• Participate in Agile ceremonies and contribute to continuous improvement initiatives.
• Experience & Qualifications
• 4+ years of experience in Data Engineering
• Strong hands-on experience with Databricks .
• Strong programming skills in Python .
• Experience designing and developing ETL/ELT pipelines.
• Experience with Azure and/or AWS cloud platforms.
• Good understanding of modern data architectures and lakehouse concepts.
• Experience with data quality, monitoring, and performance optimisation.
• Familiarity with Agile delivery methodologies
• Strong communication skills in English.
• French is mandatory Preferred Skills
• Experience with one or more of the following:
• Azure Data Factory
• Azure Data — Lake Storage
• AWS data services
• PySpark
• DataOps and CI/CD pipelines
• FinOps reporting or cloud cost optimisation
• Enterprise data governance and security standards