We are looking for an experienced Databricks Data Engineer with strong hands-on expertise in Scala and the Azure ecosystem to design, build, and optimize scalable data ingestion and processing frameworks. This role involves close collaboration with clients, architects, and cross-functional teams to translate business requirements into high-quality technical solutions.
Understand functional and business requirements and translate them into detailed technical specifications
Design and develop scalable frameworks and reusable components for data ingestion and processing using Azure Databricks
Build, optimize, and maintain ETL/ELT pipelines for large and complex datasets
Apply Spark/Scala optimization techniques to ensure performance, scalability, and reliability
Work closely with Client Data Engineering Managers to align technical solutions with business objectives
Collaborate with customer Architecture teams on solution design, code reviews, and best practices
Participate in Agile sprint-based development and deliver high-quality outputs as per project plans
Ensure code quality, performance tuning, and adherence to data engineering standards
Strong hands-on design and development experience on the Databricks platform
Proficiency in Scala with Apache Spark
Experience with the Azure ecosystem, including:
Proven experience in Spark performance tuning for large datasets
Experience designing and implementing ETL/ELT pipelines in Databricks
Strong problem-solving skills to handle complex business logic
Good communication skills with experience working directly with clients
