Responsibilities
AI Native Data Product Engineering (on Datasphere)
Design and implement governed data products using Datasphere concepts such as Spaces and shareable models/views, enabling teams to explore, transform, and share curated datasets across domains.
Build semantic models that are fit for both analytics and AI consumption (transparent entity definitions, measures, hierarchies, lineage-friendly design).
Retrieval + Grounding (RAG) over Enterprise Data
Create grounded AI experiences by connecting LLM applications to Datasphere s curated models and enterprise sources (SAP and non SAP), ensuring responses are traceable to governed data.
Engineer retrieval strategies that respect domain boundaries (spaces), freshness needs, and access controls, so AI outputs remain reliable and compliant.
Hybrid Modernization &
Migration (BW bridge patterns)
Enable transition paths from legacy warehouse investments by leveraging approaches such as reusing SAP BW models and skills with Datasphere / BW bridge, supporting phased cloud modernization.
Lakehouse style Layering &
Data Quality by Design
Implement layered design patterns (e.g., Bronze/Silver/Gold) to land raw data, cleanse/validate,



and publish analytics ready modelswhile maintaining explicit rules for what s exposed for consumption.
Embed quality controls, validation checks, and reproducible transformations as part of the delivery lifecycle.
Agentic Orchestration &
Tooling
Build data agents that can plan, call tools (query/metadata/lineage), retrieve context, and generate answers with citations—backed by deterministic checks and fallback behaviors.
Implement prompt templates, tool schemas, and protected action boundaries for enterprise-grade usage.
Evaluation, Observability &
Responsible AI
Establish offline/online evaluation loops (golden questions, regression suites, behavior tests) for conversational analytics and data agents.
Add telemetry for AI interactions (latency, grounding rate, failure modes) to improve reliability and cost efficiency.
Integration &
Collaboration
Partner closely with business, data governance, and platform teams to align data products with real decisions and operational workflows.
Drive reusable patterns and accelerators for repeatable delivery across domains.

📌 Sap Btp Datasph Bengaluru
🏢 RNR Global Certification
📍 Bengaluru