Join our Team
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