Software Engineer - Transformation Data
Cognite - AI for Industry24 days ago
Bengaluru, IndiaMid Level / Senior
Responsibilities
- Design, develop, and maintain scalable backend services and microservices for high-volume industrial data workloads.
- Build and improve distributed data pipelines using Spark, Kafka, and Flink.
- Develop reliable, high-performance APIs and backend services focused on scalability, availability, and maintainability.
- Optimize data processing, storage, and retrieval workflows for large datasets.
- Participate in system design and architecture discussions involving scalability and reliability.
- Troubleshoot production issues, identify root causes, and implement long-term performance and reliability improvements.
- Write clean, maintainable, well-tested code and participate in code reviews.
- Collaborate with Product Managers, engineers, and cross-functional teams to deliver solutions.
Requirements
- 3–6 years of experience in software engineering, backend development, or distributed systems.
- Strong programming experience in Java, Scala, or Python.
- Solid understanding of data structures, algorithms, and object-oriented programming.
- Hands-on experience with backend services, microservices, APIs, and SQL/NoSQL databases.
- Understanding of distributed systems, scalability, performance, and reliability concepts.
- Preferred: experience with distributed data technologies such as Spark, Kafka, or Flink.
- Preferred: experience with AWS, Azure, or GCP and Docker, Kubernetes, or other cloud-native technologies.
- Preferred: experience with CI/CD, observability, monitoring, and production troubleshooting in large-scale systems.
Tech Stack
Categories
BackendData Engineering
About Cognite - AI for Industry
Cognite builds an industrial data and AI platform used by energy, manufacturing, and power & utilities companies to integrate OT/IT data and deploy AI at scale. Its flagship product, Cognite Data Fusion, is sold as enterprise SaaS with services for implementation and Industrial AI agents. Founded in 2016 and privately held, the company focuses on asset-intensive operations and Industrial DataOps.