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Tier-1 brand, popular data engineer role, and metro location drive high applicant competition.
Core data engineering skills (Spark, Kafka, cloud) are highly transferable across industries.
Multiple mandatory big-data technologies and cloud experience increase technical filtering but no explicit years requirement.
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Design, develop, and implement scalable data engineering solutions using modern Big Data technologies including Apache Spark, Scala, Hive, and Kafka.
Build and maintain large-scale digital platforms, marketplaces, and data-driven applications within cloud-native and distributed systems architectures.
Participate in full software development lifecycle in Agile environments, including architecture design, coding, testing, and deployment of enterprise data solutions.
Strong experience with Big Data technologies: Apache Spark, Scala, Hive, Kafka.
Experience in distributed data processing and data pipeline development.
Proficiency with cloud platforms and cloud-native architectures.
Work Experience Required: Not explicitly mentioned in the JD.
Demonstrated expertise in scalable Big Data system design and implementation, with hands-on knowledge of Spark, Scala, Hive, and Kafka.
Experience working in Agile software development environments with cross-functional teams and enterprise-level projects.
Background in cloud-native architectures and distributed systems with a focus on data engineering and pipeline optimization.