Python Spark Scala Developer

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Data Engineering & Development

• Design, develop, and maintain scalable batch/stream data pipelines using Spark with Scala and Python.
• Implement efficient transformations, joins, aggregations, and data quality checks for large datasets.
• Build reusable frameworks/utilities to standardize pipeline patterns and reduce delivery time. Performance & Reliability
• Tune Spark jobs (partitioning, caching, shuffles, memory/executor settings) to improve performance and cost efficiency.
• Troubleshoot production issues, perform root-cause analysis, and implement preventive fixes.
• Ensure reliability through robust logging, monitoring hooks, and failure-handling strategies. Collaboration & Delivery
• Work with stakeholders to refine requirements and deliver well-documented, production-ready solutions.
• Conduct code reviews, enforce best practices, and mentor team members on Spark/Scala/Python patterns.
• Contribute to CI/CD-friendly development practices including testing, version control, and release readiness.
• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
• 5–9 years of experience in data engineering or backend development with strong hands-on delivery ownership.
• Strong proficiency in Python and Apache Spark for large-scale data processing.
• Solid experience with Scala for Spark-based development and production-grade implementations.
• Working knowledge of Hive and SQL-based data querying/processing concepts.