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Generic Software Engineer title, mid-level experience band, metro location, and broad backend/data skillset.
Core data engineering skills are transferable across industries, though industrial domain experience is moderately preferred.
Explicit 3–6 years requirement plus mandatory backend, language, and distributed-systems skills increases filtering strictness.
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Design, develop, and maintain scalable backend services and microservices handling high-volume industrial data workloads.
Build and optimize distributed data pipelines using technologies such as Spark, Kafka, and Flink.
Troubleshoot production issues and contribute to system design focused on scalability, reliability, and performance.
3–6 years of experience in software engineering, backend development, or distributed systems.
Strong programming skills in Java, Scala, or Python with solid understanding of data structures, algorithms, and OOP.
Hands-on experience with backend services, microservices, REST APIs, and SQL/NoSQL databases.
Good understanding of distributed systems, scalability, performance, and reliability concepts.
Experienced in building and operating distributed data platforms at scale, especially with Spark, Kafka, or Flink.
Familiar with cloud-native technologies and platforms like AWS, Azure, or GCP, including Docker/Kubernetes.
Skilled in production troubleshooting, monitoring, CI/CD, and collaborating cross-functionally on engineering solutions.