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Strong employer brand, mid-level (3–6 yrs), Bangalore location and broad generalist skillset increase competition.
Standard data engineering skills (ETL, Spark, AWS) are highly transferable across industries.
Explicit 3–6 years plus mandatory Java/Python, Spark, AWS, Kafka, SQL/NoSQL, and Kubernetes increases filter strictness.
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Build, optimize, and maintain scalable data ingestion pipelines and backend systems primarily using Java and Python.
Monitor and troubleshoot performance bottlenecks (CPU/Memory) in high-throughput ETL data pipelines, ensuring reliable data flow.
Work hands-on with AWS cloud infrastructure, Kubernetes deployments, and CI/CD pipelines to deliver complex features on time and maintain production stability.
3 to 6 years of professional software engineering experience focused on backend or data-intensive applications.
Strong hands-on proficiency in Java and Python programming languages.
Experience building and maintaining ETL pipelines and working with big data tools like Apache Spark.
Proven experience with AWS cloud services, containerization (Docker, Kubernetes), and CI/CD pipelines (GitLab, Jenkins).
Experienced in end-to-end ownership of complex backend or data pipeline features from design through production deployment.
Skilled in diagnosing and resolving both infrastructure-level and code-level performance issues independently.
Comfortable working in Agile teams with regular technical collaboration including code reviews and system design discussions.