Own Versant’s enterprise-wide strategy for how user, content, and advertising data is captured, governed, and activated across our Entertainment & Sports brands. Define and author enterprise standards, including event taxonomy and identity models, and embed privacy‑by‑design and industry measurement standards directly into the product control plane. Partner closely with product, engineering, analytics, and business stakeholders to drive alignment and adoption. Ensure data signals are consistent, privacy‑safe, and interoperable across analytics and CDP pipelines, powering deduplicated, cross‑platform audience insights and monetization.
Responsibilities:
- Own the measurement architecture. Lead the definition, iterative development, and cross‑organizational adoption of a multi‑year enterprise tracking and measurement architecture, including phased roadmaps, investment cases, maturity milestones, and clear success metrics spanning Versant’s Sports & Entertainment brands.
- Standardize how data is captured. Design and evolve the unified event taxonomy and end‑to‑end data collection framework, grounded in business outcomes and supported by data-layer contracts. Publish and maintain a living Solution Design Reference (SDR) as the single source of truth for technical & non-technical users, including visualized data flows into the Versant Data Platform.
- Make data usable for the business. Ensure tracking specifications support viewer behavior analysis, audience segmentation, cross‑platform deduplication, content recommendations, ad measurement, and financial modeling, aligned with relevant industry standards where applicable.
- Define durable collection patterns. Select and standardize client-side, server-side, and SDK-based collection approaches, ensuring alignment with analytics and CDP platform best practices and resilience to ecosystem and privacy changes.
- Establish data governance for collection and usage. Define and enforce standards for consent, data minimization, retention, access, lineage, KPI definitions, data dictionaries, and clear ownership models across business units.
- Operationalize privacy, compliance, and data quality. Embed GDPR, CCPA, and CPRA requirements in tagging, SDKs, and downstream activation workflows; establish change‑control and exception management processes for deviations from standards.
- Partner cross-functionally to drive adoption. Collaborate with Product, Engineering, Marketing, and Ad Sales to align data collection strategies with business goals, experimentation needs, and currency and audience measurement requirements.
- Ensure consistent instrumentation and identity resolution. Drive standardized implementation across web, app, and CTV platforms via CDP and event streaming pipelines; ensure robust routing to analytics, activation, and warehouse/BI.
- Own the operating model and implementation requirements. Stand up and manage intake, write detailed developer-ready requirements, design reviews, implementation sprints, release and QA processes, and ongoing monitoring, holding teams accountable for quality SLAs and adoption targets.
- Communicate clearly at all levels. Translate complex technical and privacy considerations into executive-level impact and risk narratives, while providing developer‑ready specifications, clear decisions, and actionable timelines.
- Measure and improve data quality at scale. Implement automated tag auditing and pre-production and production data quality checks against the SDR; define and track KPIs such as event loss rate, identity match rate, consent coverage, invalid traffic filtration, and viewability verification.
- Lead and develop the implementation function. Manage a direct report responsible for translating standards and taxonomy into sprint‑ready work, coordinating cross‑team implementation and QA, while providing guidance, removing blockers, and ensuring timely, high-quality delivery.