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.

Job Responsibilities

• Digital Analytics, Experimentation & Experience Intelligence
• Own digital product analytics, session replay, and experimentation platforms end-to-end (roadmap, governance, adoption, and value realization).
• Accountable for Amplitude (or equivalent), including event taxonomy, identity resolution, metric trees, permissions, and budget.
• Lead the Experimentation Center of Excellence across digital, CRM, and on-platform experiences, including intake, prioritization, design QA, statistical guardrails, and results arbitration.
• Operationalize digital experience signals (rage clicks, errors, latency, funnel drop-offs) into engineering and product triage with quantified business impact.
• Enterprise BI & Reporting (Restaurant, Ops, Finance, Franchise)
• Own the end-to-end BI strategy for restaurant system, operational, financial, and franchise reporting across corporate and franchise audiences.
• Define and govern KPIs and scorecards for sales, transactions, digital mix, margin, labor, service, uptime, refunds, guest recovery, and marketplace performance.
• Ensure consistent metric definitions and reconciliations across digital, finance, operations, and franchise reporting.
• Deliver executive, finance, operator, and franchise-ready dashboards with clear narratives, comparability, and trust.
• Establish service levels for data freshness, accuracy, and availability aligned to operational and financial close rhythms.
• Data Engineering & Analytics Architecture
• Own analytics data engineering for digital, restaurant, and enterprise data domains, including ingestion, transformation, and semantic modeling.
• Partner with Enterprise Data, Finance, and Operations to design scalable pipelines from POS, kiosks, aggregators, loyalty, CRM, payments, and back-office systems.
• Establish source-of-truth tables, dimensional models, and certified datasets that power BI, analytics, experimentation, and AI use cases.
• Define data quality SLAs, automated validation, monitoring, and incident response for analytics pipelines.
• Ensure analytics architecture supports privacy-by-design, franchise segmentation, and secure data sharing.
• Databricks Lakehouse, AI/BI & Genie AI
• Own the Databricks analytics roadmap and operating model, including workspace strategy, Unity Catalog, certified datasets, semantic models, Databricks metrics, AI/BI dashboards, and Genie spaces.
• Design and govern Genie AI experiences that translate natural-language questions into trusted insights, with clear data attribution, model and schema context, benchmarks, monitoring, permissions, and appropriate human review.
• Establish boundaries and control sets for enterprise AI assistants, limiting access to approved domains and certified datasets while preventing unsupported causal claims.
• Lead pilots and scale-up plans for restaurant, digital sales, market-basket, customer, promotion, labor, waste, and operational intelligence use cases.
• Enable governed access to Genie through collaboration channels such as Microsoft Teams, and use query logs and user feedback to improve semantic models and adoption.
• Manage Databricks and implementation partners through business cases, proofs of concept, capacity planning, commercial negotiation, delivery governance, and measurable value realization.
• Franchise Reporting & Trust
• Serve as the single accountable owner for franchise-facing analytics and reporting experiences.
• Ensure transparency, explainability, and consistency between corporate and franchise views of performance.
• Partner with Franchise Ops and Finance to evolve reporting based on operator needs and field feedback.
• Leadership, Governance & Vendor Management
• Lead and develop a multidisciplinary team spanning digital analytics, BI, and data engineering.
• Establish communities of practice for analytics, experimentation, and data engineering standards.
• Manage analytics, BI, and data platform vendors, including renewals, roadmaps, and ROI.
• Ensure compliance with data privacy, security, and regulatory standards (e.g., CCPA/CPRA, GDPR where applicable).
• Create cross-functional guilds and communities of practice that share Databricks and Genie AI learnings, accelerate reusable patterns, and raise data and AI fluency across KFC US.
• Translate analytical findings into operational decisions, executive narratives, prioritized roadmaps, and accountable action plans.
• Anticipate resource, data, integration, and vendor constraints; structure pragmatic proofs of concept and partner options that validate value before scaling.
• Guide customer data platform strategy and modernization, including evaluation of emerging Databricks Customer Lake capabilities and migration of customer intelligence workloads into durable enterprise platforms.

Working Relationships

• CDTO and KFC US Leadership Team
• KFC Global Data Leadership
• Restaurant Operations, Finance, Franchise Operations, and Field Leadership
• Yum! Connect AI, Data & Analytics
• Product Management, Engineering, UX, Digital Marketing
• Franchisees and Franchise Advisory Groups

Supervision of Personnel

• Exempt – 3
• Non-Exempt – 0

Knowledge and Skill RequiredMust-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.