Data Architect- GenAI

Job Description:

All the relevant skills, qualifications and experience that a successful applicant will need are listed in the following description.

We are looking for an experienced Data Architect with strong hands-on expertise in data architecture, data engineering, graph databases, Python-based data services, and AI-ready data pipelines. The ideal candidate will design and develop scalable data solutions that support GenAI applications, knowledge platforms, and AI agent consumption.

Key Responsibilities & Required Skills:

• Design scalable data architectures, data models, and ETL/ELT pipelines for structured, semi-structured, and unstructured data.
• Build data pipelines to extract, transform, enrich, chunk, and ingest documents and data into AI and knowledge platforms.
• Develop graph data models using Neo4j or equivalent graph databases , including nodes, relationships, properties, indexing, and graph queries.
• Develop Python-based data pipelines and services using FastAPI and REST APIs .
• Work with PostgreSQL, pgVector, embeddings, and vector search , integrating relational, graph, and vector data stores.
• Implement data integration, validation, metadata management, lineage, data quality, error handling, and reprocessing mechanisms.
• Collaborate with GenAI and AI agent teams to meet data ingestion, retrieval, and contextual data requirements.

Preferred Skills:

• Knowledge of GenAI, RAG, embeddings, document processing, and AI knowledge bases.
• Experience with GraphQL, graph-based APIs, and data access layers.
• Exposure to Google Gemini, Google ADK, and A2A frameworks .
• Familiarity with cloud-native data platforms and AI application architectures.
• Experience with GitHub Copilot or similar AI-assisted development tools. xhqgsiq
• Enterprise data architecture experience, preferably in banking or financial services (BFSI) , with an understanding of data governance, security, and privacy.