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. • Valuable 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 (Bengaluru)
🏢 Trigent Software
📍 Bengaluru