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Tier-1 employer, mid-level Bangalore data role with generalist title and metro location increases applicant competition.
Knowledge-graph and semantic-platform focus raises industry and domain-specific fit sensitivity.
Explicit 5+ years plus mandatory Spark, Kafka, Scala, Databricks, and AWS skills make shortlisting strict.
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Lead design and implementation of scalable data processing workflows and platform components using Spark, Kafka Streams, Kubernetes, and Scala.
Develop and maintain large-scale batch and streaming data pipelines supporting knowledge graph and semantic data products.
Mentor junior engineers and collaborate with cross-functional teams to deliver robust, high-performance data engineering solutions.
5+ years professional experience in software or data engineering focused on large-scale batch and streaming data systems.
Hands-on experience with Spark, Kafka, Databricks, Scala; Java is a plus.
Proficiency with AWS services (S3, EMR, Athena/Glue, SQS) and Infrastructure as Code (IaC).
Experience with distributed systems, semantic technologies (RDF, data modeling), and knowledge graph architectures.
Demonstrated ability to independently lead technical solutions from design through deployment in Agile environments.
Strong background in building reusable engineering platforms and implementing observability best practices.
Experience collaborating closely with product and platform teams to convert business needs into scalable data engineering solutions.