Data and Ai Solution Architect

Job Title: Data & AI Solution Architect

Work Experience: 12-15 Years

Work Location: Bengaluru

Project Role Description

The Data & AI Architect role is accountable for designing high-level, end-to-end data platform solutions that address complex business problems. You will lead the technical response for RFPs/RFIs, drive Proof of Concepts (POCs), and demonstrate how Microsoft Fabric, AI, and Data Governance can unify client data estates. You will bridge the gap between business value and technical feasibility, ensuring the proposed architecture aligns with the client's strategic objectives.

Key Responsibilities

Lead the technical solutioning for Requests for Proposals (RFPs) and Requests for Information (RFIs), creating compelling architectural diagrams, presentations, and effort estimations.

Conduct workshops with C-level executives and technical stakeholders to define problem statements and propose modern data estate roadmaps.

Architect and oversee rapid POCs to demonstrate the capabilities of Microsoft Fabric and Azure AI, proving value to prospective clients.

Design Unified Data Storage strategies using OneLake (the OneDrive for Data) to eliminate data silos and enable Direct Lake access for high-performance analytics.

Architect end-to-end analytics solutions leveraging Microsoft Fabric workloads, including Data Factory, Synapse Data Engineering, Data Science, and Real-Time Intelligence.

Design solutions that integrate Generative AI and LLMs (Azure OpenAI) within the data flow. Implement Copilot strategies within Fabric to democratize data access for business users.

Embed Data Governance by design using Microsoft Purview and Fabric's governance features to ensure data lineage, cataloging, security, and compliance are integral to the proposed solution.

Create migration strategies for clients moving from legacy Big Data platforms (Hadoop, Hive, On-prem SQL) or older Azure architectures (Gen2/Synapse PaaS) to the unified Microsoft Fabric SaaS platform.

Design API-led integration frameworks to ingest data from various source systems into OneLake.