Data Modeler

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Data Modeler

Bengaluru

Karnataka

8/3/26

Analyze customer data estates across Financial Services, Healthcare, Telecommunications, and other regulated verticals, and produce authoritative source-to-target mappings from customer physical schemas onto Industry Data Models (IDMs) — covering entities, attributes, keys, grain definitions, and business logic transformations. Define and maintain IDM mapping standards, canonical equivalence patterns, and naming conventions for each supported industry vertical — the governing artefacts that AI mapping agents use at runtime to propose and validate mappings autonomously. Define and provide behavioral ground truth for the AI data modelling agent: annotate correct mappings, flag incorrect proposals, and document the reasoning behind every accepted or rejected agent decision — forming the authoritative reference the agent is trained and evaluated against. Build and curate high-quality golden datasets for agent training and evaluation — multi-industry, multi-domain mapping examples spanning clean cases, edge cases, ambiguous entities, cross-system synonyms, and known failure modes. Design and generate synthetic data sets that faithfully reproduce the structural and statistical properties of real customer schemas without exposing customer data — enabling safe, scalable agent training, regression testing, and evaluation suite expansion. Validate AI-generated outputs: review auto-proposed data models, source-to-target mappings, and dbt/SQL transformation artefacts for correctness, completeness, and adherence to IDM and governance standards. Define, author, and govern the Semantic Data Type vocabulary — connecting physical columns to governed business concepts and data quality expectations across all supported IDM verticals. Author and maintain the Business Glossary for each