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Mid-level 3–6y, Bangalore metro, and broad Java/Python/Spark/Kafka skillset increase applicant competition.
Core data engineering skills are transferable, but specialized ETL and big-data tooling create moderate industry specificity.
Explicit 3–6 years plus mandatory ETL, Spark, cloud, and containerization skills imply high shortlisting strictness.
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Build, optimize, and maintain high-throughput data ingestion pipelines and backend systems using Java or Python.
Monitor and troubleshoot application performance issues related to CPU, memory, and database query optimization.
Collaborate in system design, conduct code reviews, manage deployments on AWS and Kubernetes, and deliver features within Agile sprints.
3 to 6 years of professional software engineering experience focused on backend or data-heavy applications.
Proficiency in Java and Python programming languages.
Experience with ETL pipeline development, Apache Spark, and both SQL and NoSQL database schema design and query optimization.
Hands-on experience with AWS cloud infrastructure, Kubernetes deployments, and CI/CD pipelines (e.g., GitLab, Jenkins).
Candidates with proven ownership of complex technical features from development to production deployment in data ingestion contexts.
Strong debugging and independent problem-solving skills for code and infrastructure issues.
Experience working in Agile environments with active participation in system design and peer code reviews.