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Senior role with niche Scala+Spark+Kafka skills at a mid-tier employer reduces applicant density moderately.
Core data engineering skills are transferable across industries, though geospatial mapping adds moderate domain specificity.
Explicit 9+ years and multiple mandatory technologies (Scala, Spark, Kafka, AWS) make filters strict.
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Develop and maintain scalable backend services and distributed data pipelines for large-scale map data processing using Scala and Apache Spark.
Lead architecture and design efforts for data processing tools that ensure quality and traceability of global navigational data.
Own end-to-end delivery including development, testing, performance optimization, and production stability in an agile environment.
9+ years of backend development experience with Scala as the primary programming language.
Production experience with distributed data processing frameworks like Apache Spark.
Hands-on experience with Kafka, AWS cloud services (EMR, Step Functions, ECS, Lambda), and SQL/PostgreSQL for data modeling and query optimization.
Work Experience Required: 9+ years as mentioned in the description.
Strong expertise in building data-intensive, event-driven backend systems with scalable and modular architecture.
Experience working on cloud-native platforms with emphasis on production readiness, monitoring, and CI/CD best practices.
Exposure to geospatial or map-related data processing and quality management systems is highly advantageous but not mandatory.