Cloud Data Engineer

We are looking for a highly motivated and detail-oriented Data Engineer to join our growing data and analytics team. In this role, the candidate will be responsible for designing, developing, optimizing, and maintaining scalable data pipelines and workflows that support enterprise reporting, analytics, and business decision-making. This role requires strong expertise in modern data engineering practices, including ETL/ELT development, data quality validation, data modeling, and cloud-based data platform implementation. The ideal candidate will work closely with cross-functional stakeholders, including business teams, analysts, architects, and developers, to ensure reliable and high-quality data availability across multiple systems. A key focus of this role will be to build robust and efficient data solutions using Azure and Databricks technologies, implement data validation and monitoring mechanisms, and proactively troubleshoot performance or pipeline issues. This position plays an important role in enabling data-driven transformation within the organization, particularly in supporting insurance domain use cases, where data accuracy, consistency, and governance are critical. The candidate is also expected to contribute within an Agile delivery model, participate in sprint ceremonies, and continuously improve data engineering processes, standards, and platform performance. Develop and maintain scalable and efficient data pipelines to ensure seamless data flow across various systems address any issues or bottlenecks in existing pipelines. Implement robust data checks to ensure the accuracy and integrity of data. Summarize and validate large datasets to ensure they meet quality standards. Monitor data jobs for successful completion. Troubleshoot and resolve any issues that arise to minimize downtime and ensure continuity of data processes. Regularly review and audit data processes and pipelines to ensure compliance with internal standards and regulatory requirements Familiar with working on Agile methodologies - scrum, sprint planning, backlog refinement etc. 3-6 years’ experience on Data Engineering role working with Databricks & Azure Cloud technologies. Bachelor’s degree in computer science, Information Technology, or related field. Strong proficiency in PySpark, Python, SQL. Strong experience in data modeling, ETL/ELT pipeline development, and automation Hands-on experience with performance tuning of data pipelines and workflows Proficient in working on Azure cloud components Azure Data Factory, Azure DataBricks, Azure Data Lake etc. Experience with data modeling, ETL processes, Delta Lake and data warehousing. Experience on Delta Live Tables, Autoloader & Unity Catalog. Preferred - Knowledge of the insurance industry and its data requirements. Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy. Excellent communication and problem-solving skills to work effectively with diverse teams Excellent problem-solving skills and ability to work under tight deadlines.