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8 days ago
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Requirements and responsibilities
About Meaningful AIMeaningful AI helps organizations unlock the value in their data. We design and build AI-driven data platforms, taking clients from raw, undocumented data environments through to canonical models, semantic layers, and analytics-ready infrastructure.What You'll DoDesign canonical data models for core business domainsDiscover and interpret schemas across complex legacy datasets (like Databricks)Reverse-engineer existing data structures and infer relationships across systemsEstablish standardized naming conventions, data definitions, and source-to-canonical mappingsCollaborate with client data teams to understand data structures, calculated fields, and transformation logicDesign semantic layers and data governance frameworksProvide architectural direction for downstream data modelsAdvise on ML-ready data productsWhat We're Looking ForRequired:Strong data modeling and schema design experience (conceptual, logical, physical)Experience with Databricks and/or Spark-based data platformsDemonstrated ability to reverse-engineer undocumented schemas and infer entity relationshipsExperience building canonical or enterprise data models in complex, multi-source environmentsSemantic layer design experience (ideally with Power BI as the downstream consumer)Comfortable working with business stakeholders to define data definitions and governance policiesEager to learn AI toolingStrongly Preferred:Experience in regulated industries with complex data environmentsExperience with Medallion Architecture (bronze/silver/gold patterns)Familiarity with enterprise transaction and accounting systemsExperience with modern AI tool setsEnvironmentOur client environments are managed with strict security controls and restricted internet access. You should be comfortable working within enterprise security constraints.
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