Senior GCP Data Architect - Autonomous Networks & AI Platform
Senior architecture role at Capgemini (Abingdon, UK) designing and governing enterprise-scale GCP data & AI platforms for telecom autonomous networks. Day to day covers BigQuery, Dataflow, Pub/Sub, BigLake, Vertex AI, plus knowledge graphs, digital twins, and GenAI/RAG/Agentic AI reference architectures.
- Compensation
- Not disclosed
- Location
- Abingdon, GB
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Architecture
- Posted
Skills
Must have
- 10+ years in enterprise data architecture with 5+ years designing large-scale cloud-native data platforms
- Google Cloud expertise: BigQuery, Dataflow, Pub/Sub, Dataplex, BigLake, Cloud Storage, Vertex AI, Cloud Composer, Spanner
- Knowledge Graph & semantic modelling
- Data engineering: ETL/ELT pipelines, real-time streaming architectures, event-driven platforms, data observability and governance
- AI & data intelligence: RAG architectures, vector databases, embedding frameworks, semantic search, feature engineering, AI-ready data platforms
- Telecom domain experience
- Security clearance: BPSS, Security Clearance, or Developed Vetting
Nice to have
- Experience with Digital Twin platforms
- Experience with Knowledge Graph implementations
- Data Mesh architectures
- LangChain, LangGraph and LlamaIndex
- Vertex AI and Gemini
- Vector databases (Pinecone, Weaviate, Milvus, Qdrant)
- Kubernetes and GKE
- Autonomous Network and AI-Ops programmes
Full description
Your role
This is a senior architecture role focused on designing and governing end-to-end GCP Data & AI platform, spanning data ingestion, governed data lake/lakehouse, data products, Knowledge Graph, Digital Twin data foundations, and Agentic AI platforms. The role requires an architect capable of shaping the complete data ecosystem rather than individual technology layers in isolation.
In this role you will play a key role in:
- Design and govern enterprise-scale GCP data platforms using BigQuery, Spanner Graph DB, Dataplex, Dataflow, Pub/Sub, BigLake and Cloud Storage.
- Develop architectures supporting GenAI, RAG, vector search, embeddings and Agentic AI platforms using Vertex AI and related technologies
- Define data models and integration patterns for Domain and Cross-Domain Digital Twins.
- Define integration patterns across OSS/BSS, network domains, Digital Twin, Knowledge Graph and AI platforms.
- Establish standards, methodologies and reference architectures for data, AI and autonomous network platforms
Your profile
- 10+ years in enterprise data architecture with 5+ years designing large-scale cloud-native data platforms.
- Google Cloud Expertise including: BigQuery, Dataflow, Pub/Sub Dataplex, BigLake, Cloud Storage, Vertex AI, Cloud Composer, Spanner
- Knowledge Graph & Semantic Modelling
- Data Engineering: ETL/ELT pipelines, Real-time streaming architectures, Event-driven platforms, Data observability and governance
- AI & Data Intelligence: RAG architectures, Vector databases, Embedding frameworks, Semantic search, Feature engineering, AI-ready data platforms
- Telecom Domain Experience
Nice-to-Have Qualifications
- Experience with Digital Twin platforms
- Experience with Knowledge Graph implementations
- Data Mesh architectures
- LangChain, LangGraph and LlamaIndex
- Vertex AI and Gemini
- Vector databases (Pinecone, Weaviate, Milvus, Qdrant)
- Kubernetes and GKE
- Autonomous Network and AI-Ops programmes
If you're excited about this role but don’t meet every requirement, we still encourage you to apply, your unique experience could be just what we need.
Make it real - what does it mean for you?
- Open access to digital learning platforms
- Active employee networks promoting diversity, equity and inclusion like OutFront, CapAbility or Women@Capgemini