Join our Team:
About this opportunity:
- Welcome to an exciting opportunity at Ericsson, where you'll step into the role of a Data Engineer working on high-volume, low-latency data platforms powering next-gen GenAI systems, AI agents, and enterprise copilots for Telecom OSS/BSS. We build production-grade systems that drive automation, intelligence, and decisioning at scale. Real systems, Real impact.
- What you will do:
- Build and operate large-scale, high-throughput data systems handling massive datasets
- Develop complex, scalable solutions using Python and Java
- Design and optimize distributed data pipelines using Apache Spark
- Engineer low-latency, high-performance data processing systems (batch+streaming)
- Work with Cassandra and OpenSearch/Elasticsearch for high availability and scale
- Develop scalable backend services and REST APIs (Spring Boot-based microservices)
- Experience to work with AWS (Kiro) / Microsoft Copilot stack
- Build RAG pipelines across network, service, customer, and operational data
- Engineer data pipelines for embeddings, vector stores,



and retrieval systems
- Implement end-to-end Data/MLOps pipelines using Docker, Kubernetes, Kubeflow, and CI/CD
- Ensure system performance, scalability, observability, and reliability
- Manage and mitigate FOSS (Free & Open Source Software) vulnerabilities using security scanning and patching practices
- The skills you bring:
Solid Python and Java expertise with experience building production-grade systems is mandatory
- Hands-on experience with Apache Spark (PySpark/Scala/Java) and distributed processing
- Proven experience in high-volume, low-latency system design and optimization
- Strong knowledge of Cassandra, OpenSearch/Elasticsearch, and NoSQL data modeling is mandatory
- Experience building scalable APIs and microservices (Spring Boot)
- Hands-on experience with cloud platforms (AWS or GCP)
- Strong working knowledge of Docker and Kubernetes
- Experience with vulnerability management and n

📌 Data Engineer (Kolkata)
🏢 Ericsson
📍 Kolkata