Data Engineer – Databricks & Azure (Remote)

About the role

Capgemini Engineering is looking for a Data Engineer with strong expertise in Databricks, Python and Azure to design, develop and optimise scalable data pipelines and analytics solutions. The position is fully remote and supports a variety of industrial digital technologies across engineering, manufacturing and supply‑chain domains.

Key responsibilities

• Design, build and maintain data replication and integration solutions using HVR.
• Develop scalable pipelines on Databricks (Spark, Delta Lake) for both structured and unstructured data.
• Implement and optimise ETL/ELT processes, ensuring data quality, integrity and performance.
• Collaborate with data scientists and analysts to enable advanced analytics and machine‑learning workloads.
• Integrate data from databases, APIs, and streaming systems, and tune Spark jobs for cost efficiency.
• Apply data governance, security and access‑control policies.
• Support CI/CD pipelines, DevOps best practices, and production‑level monitoring and troubleshooting.

Required profile

• Bachelor’s degree in Computer Science, Engineering or a related field.
• Hands‑on experience in data engineering or big‑data development.
• Strong knowledge of SQL, Oracle, SQL Server and web‑based APIs (REST/SOAP).

Required skills

• Python
• Azure (including Azure Data Factory)
• Power BI
• Databricks platform
• Apache Spark (PySpark/Scala)
• Delta Lake
• SQL & relational databases
• Java & JavaScript (preferred)
• HVR data replication
• Cloud platforms: Azure, AWS, GCP
• Data orchestration tools: Airflow, Azure Data Factory

What we offer

• Opportunity to work on cutting‑edge data solutions for global engineering projects.
• Fully remote work environment.
• Collaboration with a diverse, international team of experts.