Senior BI and Data Architect

Job Summary

Reporting to our Director, Customer Data and Identity Engineering, we are looking for a Senior BI and Data Architect with strong end-to-end data stack skills to design, build, and maintain the analytical data platform that powers reporting and decision-making across the business. Beyond traditional BI, this role will enable self-service, AI-powered conversational analytics – building the governed, well-documented semantic layer that lets business users ask questions in natural language and get trustworthy, consistent answers.

This is a hybrid position based in our Woodland Hills, CA office. You will be required to adhere to our hybrid work policy, working from our office Monday and Thursday plus one additional weekday on a weekly basis.

• End-to-end BI & data architecture and implementation
• Own BI solutions across the full data stack: data ingestion and transformation (Synapse, Databricks), analytical data models, and Power BI semantic models and reports.
• Design robust, scalable BI architectures aligned with enterprise standards.
• Act as a bridge between data engineering and business analytics, ensuring consistency and reusability across reporting tools and the conversational AI layer.
• Data modelling & analytics
• Design and maintain analytical data models (star/snowflake) optimized for reporting, performance, and natural-language querying—using clean, business-friendly naming and well-defined keys and relationships.
• Build and own Power BI semantic models with clean business definitions, reusable measures, and strong performance characteristics on Fabric capacity.
• Develop advanced DAX measures, including time intelligence, trend and variance analysis, and booking curves and demand patterns relevant to the hospitality industry.
• Conversational AI analytics & Databricks Genie enablement:
  • Design, build, and curate Databricks Genie for key business domains (e.g., bookings & demand, revenue management, operations) — selecting certified tables and metric views and authoring clear instructions, example SQL, and verified answers so business users receive trustworthy responses.
• Build and govern the Unity Catalog semantic layer (metric views) so core KPIs are defined once and reused consistently across Genie, AI/BI dashboards, and alerts.
• Make data AI/BI-ready: maintain rich table and column descriptions, a business glossary, and synonyms/entity matching so Genie reliably maps business language to the correct fields.
• Continuously evaluate and improve answer accuracy, reviewing generated SQL and refining instructions based on user feedback.
• Where valuable, extend conversational analytics into the flow of work by embedding Genie in Microsoft Teams, or applications via the Conversation API.
• Data engineering & transformations:
  • Develop data transformations using SQL and Python, and work with Databricks to prepare clean, well-modeled analytical datasets for both BI and conversational AI consumption.
  • Apply analytics-engineering best practices (layered models, clear data contracts, tested transformations).
• Business partnership & communication:
  • Work closely with business stakeholders (commercial, revenue, operations, leadership) to understand requirements, challenge assumptions, and translate needs into scalable BI and self-service analytics solutions.
  • Clearly communicate data definitions, model limitations, and trade-offs and design decisions.
  • Help drive data literacy and trust in BI outputs and AI-generated answers — including guidance on how to ask effective questions through prompt engineering and how to interpret results.
• Governance, quality & performance:
  • Ensure data quality and consistency across BI models and the AI layer.
  • Establish and enforce Unity Catalog metadata standards (table/column descriptions, tags, ownership, certification, lineage) and ensure Genie respects Unity Catalog permissions, row-level security, and column masking.
  • Optimize Power BI models for Fabric capacity usage (memory, refresh strategy, query performance).
  • Contribute to BI standards, best practices, and documentation.
  • Own a strategy around shared / certified semantic models and metric definitions that serve as the single…