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Tier-1 brand and Bangalore location increase competition, seniority and niche Spark/Scala needs reduce it.
Core data engineering skills (Spark, Kafka, Scala) are broadly transferable across industries despite automotive domain context.
Explicit 8+ years and mandatory Scala/Spark/Databricks/Kafka experience create high filtering on candidates.
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Design and deliver scalable, production-grade data-intensive applications and pipelines using Spark, Databricks, Kafka, and backend APIs.
Lead architectural decisions and technology stack selection ensuring high-quality engineering standards and robust system design.
Mentor and coach junior engineers while driving improvements in testing, observability, CI/CD, and operational reliability.
Bachelor’s degree in computer science, computer engineering, or relevant technical field; Master’s preferred.
8+ years professional software engineering experience with substantial backend and data platform work.
Strong programming expertise in Scala (preferred) or Java, with hands-on experience in Spark, Databricks, and Kafka production systems.
Experience designing APIs (REST and/or event-driven), data modeling (relational databases like PostgreSQL), and distributed system concepts.
Experienced in independently leading technical design and architectural decisions for data platforms and distributed systems.
Skilled at translating complex business requirements into scalable, high-performance data engineering solutions.
Demonstrates strong ownership, technical leadership, and ability to collaborate with cross-functional teams including architects and product owners.