Solution Architect — Data & AI Platform
New
J
JobgetherData & AI
IndiaContractSenior
Salary not disclosed
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Job Details
- Experience
- 10+ years
- Required Skills
- SQLCI/CDDatabricksGenerative AI
Requirements
- 10+ years of professional experience in solution architecture, data architecture, platform engineering, or closely related technology roles.
- Strong experience designing modern data platforms, preferably using Databricks, Delta Lake, and Unity Catalog.
- Solid understanding of lakehouse architecture, data governance, metadata management, data products, and semantic modeling.
- Practical knowledge of AI/GenAI architecture patterns, including LLMs, RAG, embeddings, vector search, semantic search, model serving, grounding, and AI evaluation.
- Experience designing or enabling agentic AI workflows, particularly for data discovery, lineage, quality, documentation, troubleshooting, or platform operations.
- Strong SQL skills and familiarity with modern data engineering and analytics ecosystems.
- Experience with CI/CD practices and automation for data and AI platform development and deployment.
- Ability to operate at a strategic level while remaining sufficiently hands-on to evaluate technologies, define architecture patterns, and guide implementation teams.
Responsibilities
- Define and drive the overall Data and AI platform architecture using Databricks, Delta Lake, Unity Catalog, and modern lakehouse design patterns.
- Develop scalable architecture patterns that enable AI-ready data products, governed analytics, and enterprise AI use cases.
- Architect secure LLM and Generative AI enablement capabilities, including RAG, embeddings, vector search, semantic search, prompt orchestration, model serving, grounding, and AI evaluation.
- Design agentic AI capabilities that can support data platform operations, including metadata discovery, catalog enrichment, lineage analysis, and data quality investigations.
- Establish architecture standards for governed data products, certified metrics, semantic layers, and consistent business definitions.
- Define approaches for integrating metadata intelligence and semantic context into AI-driven analytics and data experiences.
- Collaborate with engineering, data, AI, and business stakeholders to translate complex requirements into practical architecture solutions.
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