Job Summary:
This role is a hands-on specialist responsible for creating and maintaining a trusted, scalable semantic analytics foundation within Power BI and Microsoft Fabric. The Position has a hybrid focus on data science expertise with enterprise architecture skills to design and implement scalable, secure and business aligned data driven solutions. The position focuses on augmented analysis, enterprise-grade semantic modeling, and analytics CI/CD practices, while also building AI-powered productivity tools using Copilot CLI to improve how analytics assets are developed, documented, tested, and released. Ensures metrics are consistent, explainable, and ready for AI-assisted insight generation. This is not a management role; success comes from direct contribution, craftsmanship, and problem-solving.
Job Requirements:
Education and Work Experience:
- Bachelor's in computer science, applied mathematics, statistics or equivalent combination of education/related experience: Required
- Master's degree in data science: Preferred
- Previous hands-on experience with Power BI & Microsoft Fabric semantic models: Preferred
- Previous Practical experience with Git-based workflows for analytics assets: Preferred
- Previous experience with Cloud platform expertise in Fabric, database design, data modeling, ETL/ELT pipelines, machine learning frameworks, GPU computing, and API design: Preferred
Essential Functions:
- Design a machine learning pipeline using Fabric and Databricks that ingests sensor data, trains predictive models, and deploys them via GPU-accelerated cloud services, ensuring scalability, security, and integration with existing business systems.
- Design semantic models that are AI- and Copilot-ready, enabling: natural language exploration, automated variance and contribution analysis, narrative insights and explanations. Build reusable analysis patterns (trend drivers, productivity analysis, utilization, variance-to-plan, cohort views).
- Build architectures that can handle growing data volumes, user loads, and computational demands, often with a 3-5 year forward-looking perspective. Implement version-controlled semantic models using Git-based workflows. Translate complex business logic into clear, reusable, and performant semantic definitions.
- Partner with IT, engineers, and business leaders to align technical design with strategic objectives. Present technical concepts to non-technical stakeholders and document architecture decisions. Define and maintain deployment practices across development, validation, and production.
- Build automated checks for: measure validity and dependencies, formatting and naming standards, refresh rules and performance heuristics. Produce clear change summaries and impact notes for model updates. Reduce production risks by making semantic changes predictable, traceable, and repeatable. Create well-structured: measures and calculation groups, business-friendly hierarchies, standardized naming and formatting conventions.
- Performs other job-related duties as assigned.
