Data Engineer

Python, Spark Scala Developer

Technology->Analytics - Packages->Python - Big Data,Technology->Big Data - Data Processing->Spark,Technology->Big Data - Data Processing->Scala • 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. 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.