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Metro location, popular senior engineer title, and broad skill requirements increase candidate competition.
Specific data engineering and AWS requirements moderately limit cross-industry transferability.
Explicit 7-10 years requirement plus mandatory Java, PySpark, AWS, and Kubernetes skills enforce strict shortlisting.
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Develop, maintain, and support Java and Python-based cloud-native applications, REST APIs, and event-driven microservices on AWS.
Design and implement data processing pipelines using PySpark/Glue and Elasticsearch/OpenSearch solutions including complex search query handling.
Deploy and manage containerized applications using Docker and Kubernetes (Amazon EKS), and participate in code reviews and production support.
7-10 years of relevant experience or equivalent combination of education and experience.
Strong programming skills in Java and Python with hands-on experience in Spring Boot and REST APIs.
Experience with AWS Cloud services including API Gateway, Lambda, S3, Kinesis, DynamoDB, SNS, SQS, and SSM.
Hands-on experience with PySpark, AWS Glue, Elasticsearch/OpenSearch, Docker, Kubernetes (Amazon EKS), and PostgreSQL.
Experienced in building scalable, event-driven microservices and data engineering solutions on AWS cloud infrastructure.
Comfortable working with both backend development (Java/Python) and data processing technologies (PySpark/Glue).
Familiar with container orchestration (Kubernetes) and implementing CI/CD pipelines in an Agile environment.