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Metro Bangalore mid-level data engineer with common 3–6 year band and broad skills produces medium competition.
ETL, Spark, cloud, and backend skills are highly transferable across industries, indicating low background sensitivity.
Explicit 3–6 years plus mandatory Java/Python, Spark, AWS, SQL/NoSQL, and Kafka requirements imply high shortlisting strictness.
Design, build, optimize, and maintain scalable high-throughput data ingestion and ETL pipelines using Java and Python.
Monitor and troubleshoot system performance issues including CPU, memory, and database query optimizations for large-scale data workflows.
Collaborate in system design, perform code reviews, manage AWS cloud infrastructure, Kubernetes deployments, and CI/CD pipelines, and mentor junior engineers.
3 to 6 years of professional software engineering experience focusing on backend and data-heavy applications.
Strong proficiency in Java and Python programming languages.
Experience with Apache Spark, SQL and NoSQL databases (e.g., PostgreSQL, DynamoDB), messaging systems (e.g., Kafka, AWS SQS).
Hands-on experience with AWS services, Kubernetes, Docker, and CI/CD tools (GitLab or Jenkins).
Demonstrates ownership of complex technical features from development through production deployment in agile environments.
Has solid backend and big data engineering skills with practical experience maintaining high-throughput, large-scale ETL pipelines.
Comfortable working in cloud-native infrastructure with expertise in AWS, container orchestration, and DevOps practices.