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Tier-1 brand, mid-level data engineer role in metro with broad stack drives high competition.
Core data engineering skills are transferable, though payments and regulated transaction experience increases domain specificity.
Mandatory 6+ years plus deep Spark/Kafka/NiFi and production distributed systems experience creates 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 high-performance, fault-tolerant distributed systems handling large data volumes.
Analyze and optimize system performance, participate in troubleshooting, and collaborate with cross-functional teams to ensure production environment excellence.
Bachelor's degree in Computer Science, Engineering, or related technical field.
6+ years of hands-on experience in software development, deployment, validation, and testing 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, strong SQL and data modeling skills; experience with distributed storage systems like Apache Ozone, Ceph, HDFS, or cloud-based stores.
Experienced in operating production-grade distributed systems in cloud or hybrid-cloud environments with performance and scalability focus.
Skilled in building observability and automation frameworks, operating in data-driven, regulated, and transaction-processing enterprise settings.
Able to contribute to architecture, engineering standards, CI/CD, and mentor junior engineers for technical excellence.