We are looking for a skilled Data Engineer to design, build, and maintain scalable data pipelines and platforms.

You will work closely with data scientists, analysts, and business stakeholders to ensure reliable, high-quality data across our ecosystem.

Responsibilities :

- Design and develop robust ETL/ELT pipelines using PySpark and SQL for large-scale data processing.

- Build, manage, and optimise data workflows on Databricks, including notebooks, jobs, and cluster configurations.

- Collaborate with analytics and ML teams to deliver clean, well-documented datasets.

- Monitor pipeline performance, troubleshoot failures, and ensure data quality and integrity.

- Define and implement data governance and best practices across the data platform.

- Participate in design reviews and contribute to architectural decisions.

Requirements :

- 4 - 6 years of hands-on experience in data engineering or a related role.

- Strong proficiency in PySpark for large-scale distributed data processing.

- Advanced SQL skills - query optimisation, window functions, CTEs, and complex joins.

- Solid experience with Databricks - Delta Lake, workflows, Unity Catalog preferred.

- Experience working with cloud platforms (AWS/Azure).

Nice to have :

- Experience with streaming frameworks such as Apache Kafka or Spark Streaming.

- Exposure to ML pipelines and feature engineering workflows.