Databricks Engineer

Job Title: Databricks Data Engineer Experience: 5 to 8 Years Location: Bangalore, India Work Mode: Onsite Job Type: Full Time We re hiring for one of the top IT services companies. SPADTEK Solutions is proud to collaborate with leading IT organizations to source exceptional talent for their full-time and Contract positions. Client/Implementation Partner is a globally recognized IT services and consulting company, trusted by Fortune 500 clients and enterprises worldwide. With a strong presence across cloud, data engineering, AI, and digital transformation and is known for delivering cutting-edge solutions that drive business growth and innovation. Working on enterprise-scale projects with global clients. Exposure to next-gen technologies across cloud, data, and digital platforms. A culture that values continuous learning, collaboration, and career growth. Being part of a company consistently ranked among the top IT employers. If you are an experienced professional seeking a long-term career opportunity with one of the industry s most respected names, this is your chance to join top IT services company through SPADTEK Solutions. Key Responsibilities Design, develop, and maintain scalable data pipelines using Databricks and PySpark. Build and optimize ETL/ELT workflows for large-scale data processing. Implement and manage data quality frameworks to ensure data accuracy, consistency, and reliability. Develop and maintain workflow orchestration solutions using Databricks Workflows and/or Airflow. Work with Delta Lake, Unity Catalog, and Databricks platform components to support data governance and analytics. Collaborate with cross-functional teams to understand business requirements and deliver data solutions. Optimize Spark jobs and SQL queries for performance and scalability. Support data integration, transformation, and reporting initiatives across the organization. Required Skills Strong experience with Databricks (Workflows, Delta Lake, Unity Catalog, Genie). Hands-on experience with PySpark, Spark SQL, Python, and SQL. Experience implementing Data Quality Frameworks (DQX). Expertise in workflow orchestration using Airflow and/or Databricks Workflows. Strong understanding of data engineering concepts, ETL/ELT processes, and data warehousing. Experience working with large-scale distributed data processing environments. Good to Have Skills Experience with cloud platforms such as AWS, Azure, or GCP. Knowledge of CI/CD practices and DevOps methodologies. Familiarity with data governance and data cataloging tools. Exposure to real-time data processing and streaming technologies. Experience working in Agile development environments. Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.