Build and optimize scalable data pipelines using Databricks, PySpark, Spark, and Azure Data Factory. Analyse, clean, and organize raw data from multiple structured and unstructured sources. Develop and maintain ETL/ELT workflows following best engineering and DevOps practices. Implement CI/CD pipelines using GitHub and Azure DevOps. Deploy and orchestrate workloads using Docker and Kubernetes. Develop solutions aligned to enterprise data models, DataVault methods, and architectural standards. Ensure data quality, data governance, GDPR compliance, and metadata management. Use tools like QuerySurge for data testing and validation. Collaborate with teams using Agile/Scrum frameworks and tools like JIRA, Confluence, and SharePoint. Support production deployments, troubleshooting, and operational excellence for cloud data services

Hands-on expertise in Azure, Databricks, Synapse, Python, SQL, Spark, and PySpark. Strong experience with CI/...