Data Engineer

Job Summary We are seeking a highly skilled Data Engineer with 9+ years of experience to design, build, and optimize scalable data pipelines and cloud-based data solutions. The ideal candidate will have strong expertise in Azure, Databricks, ADF, Data Engineering principles, and exposure to PowerBI in Banking domain projects. Mandatory Skills Azure, Databricks, ADF, Data Engineering, SQL, Power BI(basic). Key Responsibilities . Design and build scalable ETL/ELT pipelines using Azure and Databricks. . Automate data workflows and optimize performance across data systems. . Develop and maintain data models supporting analytics and reporting. . Collaborate with cross-functional teams including BI, Data Science, and Business stakeholders. . Implement best practices in data quality, governance, and security. . Troubleshoot issues and optimize system reliability and performance. . Support BI teams with data access, semantics, and structured data layers. Qualifications Bachelor's degree in Computer Science, Engineering, or related field. Technical Skills . Azure (ADF, Data Lake, Function Apps) . Databricks (PySpark, Delta Lake) . SQL / NoSQL . CI/CD with Azure DevOps / GitHub . Power BI basics for data validation . Cloud architecture understanding . Experience with CI/CD automation, Python advanced, Banking/Financial Services domain. Soft Skills Excellent communication, analytical thinking, stakeholder management, problem solving, documentation ability. Work Experience . Minimum 9 years of experience as a Data Engineer in enterprise environments.

Key Result Areas (KRA): . Timely delivery of data pipelines and models . Data quality compliance across projects . Platform optimization and stability . Cross-team collaboration effectiveness Key Performance Indicators (KPI): . Pipeline delivery success rate . Data quality issue reduction % . System/performance improvement % . Stakeholder satisfaction score