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/CD frameworks, GitHub, and Azure DevOps. • Positive understanding of data warehousing, data modelling, cloud infrastructure, and data architecture. • Experience with data quality, data governance, and GDPR compliance. • Strong problem-solving, communication, and stakeholder management skills. • Experience in Agile/Scrum methodologies.

Base Python, PySpark, Spark, SQL • Azure (Databricks, Synapse, ADF, Azure DevOps) • CI/CD (GitHub, Azure DevOps) • Docker & Kubernetes • DataVault, Data Warehousing, Data Modelling • Data Governance, Data Quality, GDPR • Power BI, Jupyter Notebook • Oracle DB, Postgres

📌 Azure data engineer (India)
🏢 Trigent Software
📍 India