Azure Databricks Developer (Remote) - Data Engineering & AI

Atos SE; United Kingdom; Hybrid; GBP 60,000 - 90,000; Full time

Benefits offered by this job

25 days paid leave

Pension scheme

Private medical cover

Income protection

Life assurance

Flex benefits program

Disability confident employer

Job summary

Atos is seeking an Azure Databricks Developer to design, develop, and support scalable data engineering solutions on the Azure data platform. You will build data ingestion, transformation, and processing pipelines to enable advanced analytics, AI, and BI capabilities.

Collaborate with Data Architects, Data Engineers, and Solution Architects to deliver trusted data products while ensuring security, governance, and operational standards are met.

Qualifications

• Experience building enterprise-scale ETL/ELT pipelines within Azure environments.
• Strong Python and SQL development skills.
• Experience with Azure Data Lake Storage Gen2 and Azure Data Factory or Microsoft Fabric Data Factory.
• Git version control and software engineering best practices.

Responsibilities

• Design, develop, and optimise scalable data pipelines using Azure Databricks, PySpark, Spark SQL, and Delta Lake.
• Build robust ETL/ELT solutions and data ingestion frameworks supporting batch and streaming workloads.
• Integrate data from multiple sources, including Azure SQL Database, Azure Data Lake Storage Gen2, Microsoft Fabric, APIs, SaaS platforms, and on-premise systems.
• Implement data quality, validation, monitoring, and governance controls across the data lifecycle.
• Support platform engineering activities, including CI/CD implementation, environment promotion, performance optimisation, and operational support.

Tools

Azure Data Factory

Microsoft Fabric Data Factory

Azure Data Lake Storage Gen2

Job description

Atos is seeking an Azure Databricks Developer to design, develop, and support scalable data engineering solutions on the Azure data platform. You will build data ingestion, transformation, and processing pipelines to enable advanced analytics, AI, and BI capabilities.

Collaborate with Data Architects, Data Engineers, and Solution Architects to deliver trusted data products while ensuring security, governance, and operational standards are met.