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 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.