Director of Enterprise Intelligence

Purpose of The Job

Own and integrate digital analytics, experimentation, business intelligence, data engineering, and the Databricks Lakehouse into a single enterprise-grade decision platform for KFC US. Evolve that platform to deliver governed self-service analytics and natural-language insight experiences through Databricks AI/BI and Genie AI, including secure Microsoft Teams access where appropriate. This role is accountable for trusted restaurant, operational, financial, customer, and franchise reporting; certified metrics and semantic models; and the productionization of advanced analytics and AI use cases such as recommended ordering, restaurant-level forecasts, cook projections, demand signals, promotion analysis, and customer intelligence. The mandate: one measurement backbone, consistent definitions, AI-ready production pipelines, responsible-AI controls, and insight experiences—dashboards, narratives, agents, and natural-language queries—that improve digital growth, restaurant performance, franchise confidence, and profitable decision-making.

Knowledge and Skill Required
Must-Haves
- 12+ years in analytics, BI, data engineering, or applied decision science, with 6+ years leading enterprise teams and platforms.
- Proven ownership of production BI, analytics, and data platforms supporting operational, financial, and franchise reporting at scale.
- Strong experience with digital analytics and experimentation platforms (e.g., Amplitude or equivalent), including metric trees and causal measurement.
- Deep SQL expertise; strong understanding of data modeling, pipelines, analytics engineering, and semantic layers.
- Demonstrated ability to establish and govern KPIs across digital, finance, operations, and franchise contexts.
- Experience partnering with applied AI / data science teams to productionize models into business workflows.
- Familiarity with LLM- and natural-language–based analytics patterns, including metric grounding, explainability, and guardrails over certified datasets.
- Executive-, operator-, and franchise-level communication skills; ability to translate analytics and AI outputs into trusted, actionable decisions.
- Hands-on knowledge of Databricks Lakehouse capabilities, including SQL, Unity Catalog, data and AI governance, semantic modeling, AI/BI dashboards, Databricks metrics, and Genie AI spaces or agents.
- Demonstrated ability to ground natural-language analytics in certified data through attribution, metadata, metric definitions, model context, benchmarking, monitoring, permissions, and responsible-AI guardrails.
- Experience leading proofs of concept from use-case definition and vendor alignment through validation, adoption, production readiness, and value measurement.
- Strong customer and restaurant intelligence orientation, with the ability to connect digital behavior, transaction, operational, financial, and customer data to practical business decisions.
Nice-to-Haves
- QSR, retail, or multi-unit franchise experience.
- Experience integrating POS, kiosk, aggregator, loyalty, labor, and financial systems.
- Exposure to forecasting, optimization, or recommendation systems (e.g., demand forecasting, recommended ordering, labor or cook projections).
- Experience enabling natural-language query or AI-assisted insight experiences over enterprise data.
- Familiarity with modern BI, semantic modeling, and metrics-layer approaches.
- Experience embedding governed Databricks Genie experiences in Microsoft Teams or comparable collaboration channels.
- Familiarity with customer data platforms, tokenized customer data, Customer 360 modernization, and migration or decommissioning strategies.
- Experience building analytics or AI guilds, training business users, and scaling self-service adoption across functions.
- Commercial and delivery experience with Databricks and systems-integration partners, including sponsorship models, low-cost pilots, resourcing, and ROI evaluation.

Salary Range: $195,200 to $215,000 annually + bonus eligibility and stock-based compensation. This is the expected salary range for this position. Ultimately, in determining pay, we'll consider the successful candidate’s location, experience, and other job-related factors.