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Bengaluru metro and broad data-platform skills increase competition despite seniority and specialized requirements.
Core data engineering and streaming skills transfer well, though enterprise storage/AI context adds moderate bias.
Explicit 8+ years requirement plus mandatory Java/Python, Kafka, Spark, Kubernetes and platform experience raises strictness.
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Architect and lead end-to-end data analytics engineering solutions involving customer analytical needs and AI-enabled automation.
Design, develop, and support batch processing and streaming data pipelines using Java/Python and big data technologies.
Deploy and maintain applications on Kubernetes/Edge platforms with CI/CD pipelines, collaborating with cross-functional teams.
Bachelor’s or Master’s Degree in Computer Science or Software Engineering.
Minimum 8+ years of professional experience in software/data engineering roles.
Proficiency in Java and/or Python programming, database technologies (SQL/NoSQL), and big data technologies like Hadoop and Hive.
Experience with Kubernetes, batch and streaming pipeline design, and familiarity with AI integration concepts (e.g., MCP).
Experienced architect with hands-on leadership in building scalable data analytics and AI automation platforms.
Strong background in integrating AI systems with enterprise tools and building end-to-end data pipelines using Spark, Kafka, and cloud services.
Comfortable working in agile environments with test-driven development and guiding teams to solve complex technical problems.