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Mid-senior data engineering in Bangalore with broad required skills and a known brand drives high competition.
Skills transfer across industries, but Spark/Kafka/AWS expertise favors candidates from data-platform backgrounds.
Explicit 7–8 years plus mandatory Java/Python, Spark, AWS, Kafka, and Kubernetes makes shortlisting strict.
Lead design, architecture, and implementation of high-throughput data ingestion systems and ETL pipelines.
Provide technical leadership and mentorship to engineering teams, driving best practices and technical excellence.
Own full software development lifecycle including system design, data analytics, deployment, and infrastructure management.
7 to 8 years professional software engineering experience with at least 1-2 years in leadership or architectural role.
Expert proficiency in Java and Python for backend and data engineering tasks.
Strong hands-on experience with big data tools (Apache Spark), SQL and NoSQL databases, message brokers (Kafka, AWS SQS, RabbitMQ).
Extensive experience with AWS cloud services, containerization (Kubernetes, Docker), CI/CD pipelines (GitLab or Jenkins), and Infrastructure as Code tools (Terraform or CloudFormation).
Experienced technical leader skilled in scaling high-volume data ingestion or streaming platforms.
Strong command over system design, data structures, and algorithms with problem-solving emphasis.
Proven ability to work in and lead Agile/Scrum teams, effectively communicating complex technical concepts to diverse stakeholders.