• Design and implement semantically consistent, scalable 360 data models that integrate data across domains. • Build and maintain transformation pipelines that apply cleansing, standardization, enrichment, and derived logic to domain datasets. • Write production-quality, testable code in SQL and Python (or equivalent)—delivering performant and maintainable data assets. • Work closely with domain experts, data scientists, and product stakeholders to translate business concepts into interpretable, decision-ready data models. • Implement logic for classifications, KPIs, scoring algorithms, and business rules, ensuring traceability and data lineage. • Help define and enforce standards for data modeling, documentation, and governance within the semantic layer. • Collaborate across teams to integrate with ingestion, MDM, and data product layers.