Spark Scala Developer

Job description

Technology->Big Data - Data Processing->Spark,Technology->Java->Apache->Scala Data Engineering & Development - Design, develop, and maintain Spark-based batch processing pipelines using Scala for large datasets. - Implement efficient transformations, aggregations, and joins, ensuring correctness and scalability. - Write optimized SQL for data extraction, validation, and reconciliation across sources and targets. Performance, Quality & Reliability - Tune Spark jobs (partitioning, caching, shuffles, memory/executor settings) to improve runtime and cost efficiency. - Build data quality checks and validations to ensure accuracy, completeness, and consistency of outputs. - Troubleshoot production issues, perform root-cause analysis, and implement preventive fixes. Collaboration & Delivery - Work with stakeholders to understand data requirements and translate them into technical solutions. - Participate in code reviews, follow engineering best practices, and contribute to reusable components. - Document pipelines, logic, and operational runbooks for maintainability and onboarding. - Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience). - 5–9 years of overall experience with strong hands-on development in Spark and Scala. - Solid experience writing and optimizing SQL for analytics and data processing use cases. - Strong understanding of distributed processing concepts, data transformations, and performance considerations. - Ability to debug and resolve issues in data pipelines with a focus on reliability and quality.