Job Description

Job Description

Job 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:

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

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