Senior BI and Data Architect

• 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 source of truth across Power BI and Databricks Genie. 

Job Requirements: 

• Strong end-to-end BI experience across data engineering, modeling, and reporting. 

• SQL – Expert: Able to design, optimize, and troubleshoot complex analytical queries; deep understanding of joins, CTEs, window functions, aggregations, and performance tuning; comfortable validating AI-generated SQL. 

• Python – Advanced: Experience building production-grade data transformation and analytics workflows using PySpark/Pandas; strong understanding of data quality, automation, testing, and scalable data processing in Databricks. 

• DAX – Strong Working Knowledge: Able to develop complex measures and KPIs, including time intelligence, trend and variance analysis; understands evaluation context, filter propagation, and performance optimization within Power BI semantic models. 

• Power BI: semantic model design, performance optimization, Fabric capacity awareness. 

• Databricks SQL and Unity Catalog – hands-on experience with catalogs, schemas, governance, lineage, and permissions. 

• Dimensional / semantic data modeling with clean, business-friendly naming and well-defined keys and relationships (the foundation for reliable natural-language querying). 

• Strong data-documentation discipline (descriptions, business glossary, certified definitions). 

• Experience working with financial / accounting data. 

• Proven ability to communicate effectively with business stakeholders.. 

What We Offer You: 

• Highly competitive compensation plan.  

• Salary range $190,000-$220,000 annually determined by a myriad of factors including, but not limited to, years of experience, depth of experience, and other relevant business considerations.