Data Engineer

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.

Responsibilities

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

Requirements

Strong 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 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

Nice to have

Telecom OSS/BSS domain knowledge (business + data); Experience with Databricks, Snowflake, or similar platforms; Understanding of AI observability, explainability, and responsible AI