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Tier-1 brand and metro location increase competition, but specialized senior skillset narrows applicant pool.
Highly domain-specific platform and distributed-systems expertise reduces cross-industry transferability.
Explicit 10+ years plus mandatory deep distributed data platform technologies increases shortlisting strictness.
Provide technical leadership and define architecture for large-scale data platforms and distributed systems spanning multiple teams.
Design and build scalable, reliable backend services and data processing architectures using Java, Python, Apache Spark, Flink, Airflow, and Kubernetes.
Drive platform improvements in reliability, performance, and developer productivity while influencing long-term technical strategy and architectural standards.
10+ years of software engineering experience with large-scale distributed systems or data platforms.
Deep expertise in Java and strong hands-on experience with Apache Spark, Flink, Hadoop ecosystem (HDFS, Hive, YARN), and Python.
Significant production experience with Kubernetes, containers, distributed systems concepts, and workflow orchestration (Apache Airflow or similar).
Work Experience Required: 10+ years; Notice Period: Not explicitly mentioned in the JD.
Senior individual contributor with proven success leading architecture and technical decisions across multiple teams or platform initiatives.
Strong background in designing petabyte-scale data platforms including batch and real-time processing architectures.
Experience with multi-tenant platform design, data governance, observability, and modern data lake/lakehouse technologies (e.g., Apache Iceberg).