Key Responsibilities:

- Design, develop, and maintain scalable Azure data engineering solutions using Azure Data Factory, Databricks, Spark, and related Azure services.
- Develop and optimize complex SQL/T-SQL queries, data pipelines, ETL/ELT processes, and data transformation workflows.
- Implement robust CI/CD pipelines and follow strong software engineering, coding, testing, and deployment practices.
- Build and manage data solutions using Azure Databricks/Spark and integrate data from multiple enterprise sources.
- Collaborate with data engineers, software engineers, architects, and business stakeholders to deliver secure, scalable, and high-performance data platforms.

Skills Required:

- - 10+ years of experience as a Software Engineer or Data Engineer, with a degree in Engineering, Computer Science, or a related technology discipline.




- Robust hands-on expertise in Azure Databricks and Apache Spark, with Azure Data Factory experience being mandatory.
- Strong proficiency in SQL/T-SQL and experience developing optimized queries, data models, and transformation processes.
- Strong knowledge of CI/CD, DevOps, software engineering practices, and automated deployment methodologies.
- Experience with Microsoft Azure data services, including Synapse/Azure SQL DW, Analysis Services, Cosmos DB, Event Hubs, Power BI, and Azure ML; Azure certification(s) or equivalent preferred.

Please drop your CV to [email protected]

📌 Senior Data Engineer (DataBricks) (Melbourne)
🏢 Kaizen Global Technologies
📍 Melbourne