Key Responsibilities Design and develop real-time data pipelines using Kafka, Spark, AWS Kinesis , and related technologies. Build and support scalable data processing solutions on AWS . Modernize legacy ingestion frameworks using cloud-native services. Develop and optimize large-scale distributed data processing systems. Troubleshoot and support production data platforms and streaming applications. Collaborate with cross-functional teams on enterprise data integration initiatives. Required Skills & Experience 10 years of experience in Data Engineering, Software Engineering, or related fields. Strong expertise in AWS Cloud Services and cloud-native architectures. Hands-on experience with Apache Spark (Scala & PySpark) . Strong knowledge of the Hadoop Ecosystem and distributed computing. Experience with Kafka , streaming technologies, and real-time data pipelines. Experience with AWS Kinesis, Kinesis Firehose, Flume , or similar ingestion platforms. Strong programming skills in Python, Scala, and Java . Experience with Big Data, Enterprise Data Warehousing, and Distributed Systems .
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