Staff Engineer, Big Data Engineer (Telangana)

We're Nagarro. We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale across all devices and digital mediums, and our people exist everywhere in the world (17500 experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in! REQUIREMENTS: - Total experience: 7+ years. - Excellent knowledge and experience in Azure Big Data Engineer role. - Strong working experience with architecture and development in Spark, Python, Databricks, Any Cloud (AWS/Azure), GIT, Technical leadership, Airflow, SQL. - Hands-on expertise in Databricks (PySpark / Spark SQL). - Solid experience in designing and building ETL/ELT pipelines. - Proficiency in Apache Airflow for workflow orchestration. - Strong knowledge of SQL, data transformations, and data modeling. - Experience with Git and version control best practices. - Exposure to DevOps practices (CI/CD, automated deployments). - Solid understanding of data warehousing and lakehouse concepts. - Strong problem-solving skills with a solution-first mindset. - Excellent communication and stakeholder management skills. RESPONSIBILITIES: - Design, develop, and optimize ETL/ELT pipelines for large-scale data processing. - Lead the implementation of scalable data pipelines and lakehouse architectures using Databricks. - Translate business requirements into efficient ETL workflows and data solutions. - Drive solution architecture and data design decisions, not just development execution. - Build and orchestrate workflows using Apache Airflow. - Implement data ingestion, transformation, and loading processes from multiple structured and unstructured sources. - Ensure data quality, validation, lineage, and governance across ETL pipelines. - Implement and manage CI/CD pipelines using Git and DevOps practices. - Optimize data pipelines for performance, scalability, and cost efficiency. - Collaborate with business stakeholders, analysts, and engineering teams to define data strategy and ETL standards. - Mentor team members and provide technical leadership across projects. - Identify bottlenecks and proactively propose innovative ETL and data platform improvement .