Job Description
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
Develop MCP-based applications and integrations with enterprise systems
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:
Strong Python and Java expertise with experience building production-grade systems
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
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 non functional features ( alarm , logging , fault management etc.)
Good understanding of LLMs, embeddings, RAG, and GenAI data pipelines
Exposure to developer copilots / AI-assisted coding tools
Good to have:
Telecom OSS/BSS domain knowledge (business + data)
Experience with Databricks, Snowflake, or similar platforms
Understanding of AI observability, explainability, and responsible AI