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Strong Tier-1 brand, mid-level generalist data role, and Pune metro drive high candidate competition.
Core Spark/Kafka data skills are transferable, but payments and regulated experience increase domain specificity.
Mandatory 6+ years plus Spark/Kafka/NiFi and production distributed-systems implies high shortlisting strictness.
Develop, test, validate and maintain scalable batch and real-time data processing applications using Apache Spark, Kafka, and NiFi.
Build validation suites and reusable frameworks to support fault-tolerant distributed data systems handling large data volumes.
Collaborate across teams to design solutions, optimize system performance, and ensure operational excellence for production-grade distributed systems.
Bachelor's degree in Computer Science, Engineering or related technical field.
6+ years of hands-on experience with software deployment, testing, validation, and development of large-scale data-intensive applications.
Strong expertise in Apache Spark (Batch and Structured Streaming), Apache Kafka, and Apache NiFi.
Proficiency in Scala, PySpark or Python; plus experience with distributed storage systems like Apache Ozone, Ceph, HDFS, or cloud object stores.
Experience operating and troubleshooting production-grade distributed systems in cloud or hybrid-cloud environments.
Background in building scalable, resilient data pipelines and validation platforms using event-driven architectures.
Able to contribute to architecture, code reviews, CI/CD processes, and mentor junior engineers within complex, data-driven technology environments.