Back
Generalist backend title, mid-level experience range, and metro location drive high competition.
Core backend and data-processing skills are transferable, but industrial-domain preference raises sensitivity moderately.
Explicit years plus required backend and distributed-systems skills create moderately strict filtering.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and maintain scalable backend services and microservices handling high-volume industrial data workloads.
Build and optimize distributed data pipelines using Spark, Kafka, and Flink, focusing on scalability, availability, and maintainability.
Troubleshoot production issues and contribute to system design and architecture to enhance system performance and reliability.
1–3 years of experience in software engineering, backend development, or distributed systems.
Strong programming skills in Java, Scala, or Python with sound knowledge of data structures, algorithms, and OOP.
Experience with backend services, REST APIs, microservices, and SQL/NoSQL databases.
Understanding of distributed systems concepts including scalability, performance, and reliability.
A mid-level engineer experienced in building and maintaining scalable backend systems for large industrial data platforms.
Familiarity with distributed data processing technologies like Apache Spark, Kafka, or Flink and cloud-native tooling (AWS/Azure/GCP, Docker, Kubernetes).
Capable of troubleshooting at production scale and contributing strategically to architecture decisions in a cloud-native environment.