Manager, Semantic Layer Engineering

Manager, Semantic LayerEngineering

Who are we looking for?

Choice Hotels, one of the world’s largest lodging franchisors,is looking for a Manager, Semantic Layer Engineering to build andmaintaina semantic layer,a single sourceof truth for business metrics across reporting, operations, and AI.TheAdvanced Analyticsteam at Choiceis the team thatmakes sure everyone across the company — from the franchise owners running our hotels to our commercial teams and senior leaders — is working from the same trusted numbers, whether those numbers show up in a report, an operational system, or an AI assistant. As a key member of ourAdvanced Analytics team, you willbuildthegoverned, machine-readable metric definitions thatconsolidatelogic across dashboards and spreadsheets intoonecertified foundation every report, system, and AI consumer can trust.

Are youa hands-on data leader who thinksinmetric definitions, holds a high bar for governance and documentation, and is energized by turning inconsistent business logic into trusted,code-basedstandards? We invite you to apply today for ourManager, Semantic Layer Engineeringrole and#MakeItYourChoice.

YourResponsibilities

Semantic Layer Architecture & Metric Quality

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Build andmaintainthe enterprise semantic layer as the default source forgovernedmetrics consumed by dashboards, operational systems, data science, and AI agents, following established semanticlayerand metrics tooling standards set by governance leadership.

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Implement metric definitions as version-controlled, tested, reusable logic — including SQL, transforms, and joins against AWS Redshift, S3, and other systems — in alignment with established business meaning and product-defined governance criteria.

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Execute performance, reliability, and cost optimization tasks for metric query execution, following established observability practices and escalating significant infrastructure decisions for supervisor review.

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Operate automated test coverage, SLA monitoring, lineage tracking, anomaly detection rules, and incident response processes for enterprise-certified metrics, following documented quality standards.

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Review proposed changes to enterprise-certified metric definitions and support technical change approvals in coordination with the defining product manager, ensuring all updates follow established change management protocols and propagate through the semantic layer.

Metric Lifecycle & Governance Operations

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Execute the metric certification lifecycle, administering promotion gates through which metrics graduate from exploration to product-scoped use to enterprise certification based on usage, quality, and cross-team impact.

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Workwith product managers under a shared ownershipmodel — productdefines the metric need, meaning, quality thresholds, and freshness expectations — and execute implementation, monitoring, and enforcement activities.

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Identify metric inconsistencies within assigned functional areas, consolidating duplicate and conflicting metric logic into shared, governed definitions (e.g., a single enterprise definition of RevPAR), and escalating cross-team conflicts that cannot be resolved at the team level to the Senior Director for governance review.

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Document workflows, build processes, and approval paths for metricproposal, validation, certification, and consumption.

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Maintainaccuraterecords of metric lifecycle status, quality results, and open issues, providing regular and ad hoc status updates to the Senior Director to support governance oversight.

AI Enablement & Trusted Consumption

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Expose governed metrics and business context to BI platforms (Tableau), operational systems, data science, and AI agents, following established integration patterns so that new products, reports, and AI consumers inherit trusted definitions automatically.

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Maintain governed business context within the supporting data catalog so that generative AI applicationsoperateon certified business