Lead Risk Analytics Consultant - Data Architecture & BI Enablement

• Drive scalable, self-serve BI solutions that deliver actionable insights and business value through advanced analytics, and automation to make actionable insights, trends, recommendations, or contribute to large-scale planning that has a broader impact
• Enable self-service curated datasets and semantic layers for business stakeholders. Define and maintain semantic models, data dictionaries, and KPIs
• Lead data consolidation and rationalization across a complex ecosystem, transforming hundreds of disparate source tables into curated, governed, and business-ready datasets that minimize redundancy and eliminate manual data pulls
• Own the end-to-end data consumption architecture, defining how curated datasets, semantic models, and data access layers are structured and integrated with BI tools and AI-driven query interfaces
• Provide hands-on enablement and training to business stakeholders and BI users in Power BI, focusing on how to effectively use curated datasets and semantic models
• Partner with Technology teams to implement scalable pipelines and datasets in Microsoft Fabric (Lakehouse)
• Design datasets for high-performance consumption across large-scale data volumes (millions to billions of rows)
• Act as the primary business-side architectural counterpart to the Technology execution team building data models and pipelines
• Provide clear execution artifacts, including dataset specifications, mapping logic, acceptance criteria, test scenarios, and performance targets

5+ years of Risk Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

• Experience with Microsoft Fabric (Lakehouse, Direct Lake, semantic models)
• Strong SQL, Power BI knowledge, with emphasis on leveraging semantic models and curated datasets rather than report/dashboard development
• Proven ability to design data solutions that eliminate manual data pulls and reduce dependency on centralized reporting teams
• Experience working with large-scale datasets, and Parquet file structure
• Excellent communication, organizational, and planning skills
• Experience in collaborating with both technical and non-technical partners with a problem-solving mindset
• Experience in Capital Markets and Risk Management