Digital Analytics Lead

The Digital Analytics Lead owns and advances the organization’s Digital Analytics capability over the long term. This role defines the standards, frameworks, and governance that ensure user behavior is measured and reported consistently, accurately, and at scale across products and platforms.

This role serves as the organization’s subject matter expert in digital and behavioral analytics and is responsible for establishing and maturing this capability in close partnership with Data Engineering, Data Governance, and Business Intelligence teams. Serving as a lead-level individual contributor, the Digital Analytics Lead partners closely with UX, Product, Engineering, and Strategic Leadership to translate behavioral data into actionable insight aligned to inform software product decisions and achieve business outcomes.

• Define and evolve behavioral measurement frameworks aligned to product, UX, and business goals.
• Establish priorities and maturity roadmaps for behavioral and digital analytics across platforms and initiatives.
• Define and govern behavioral metrics that reflect software utility, usability, user success, and outcomes.
• Consult with cross-functional teams to recommend appropriate analytics tools, metrics, and reporting approaches, advising on measurement strategies based on efficiency, implementation effort, data availability, and insight value.
• Evaluate, pilot, and apply analytics tools and platforms to support measurement goals, usability, data quality, and decision impact.
• Make hands‑on recommendations informed by direct use of analytics tools and data, not abstract evaluation alone.
• Serve as a trusted advisor to UX, Product, Engineering, and Business leadership on behavioral metrics interpretation and appropriate tool usage.
• Act as the central steward for disciplined, consistent, and decision focused measurement practices.

• Directly design, implement, and maintain event taxonomies, tagging strategies, naming conventions, and implementation standards.
• Partner hands‑on with Engineering to implement analytics instrumentation when application code changes are required.
• Personally configure, test, validate, and audit analytics platforms (e.g., GA4, GTM, behavioral analytics tools).
• Identify and remediate tracking gaps, data inconsistencies, and implementation issues.
• Establish and run processes for ongoing behavioral data quality monitoring and validation.
• Ensure analytics implementations remain scalable, reliable, and production ready over time.

• Work hands‑on with Data Engineering, Data Governance, and Business Intelligence teams to ensure behavioral data is structured, integrated, and usable across enterprise systems.
• Define and validate behavioral data requirements for ingestion into enterprise data platforms (e.g., data warehouses and BI tools).
• Contribute directly to event schemas, data models, and patterns that connect behavioral data across platforms, sessions, and journeys.
• Ensure behavioral analytics implementations align with enterprise data architecture and downstream analytics needs.
• Serve as an active cross‑functional bridge between UX, Product, Engineering, and Data teams.

• Hands‑on analysis of behavioral data to generate actionable insights that inform product, UX, and business decisions.
• Design, build, and maintain dashboards and performance views that surface meaningful behavioral patterns.
• Use query based analysis, automation, and AI assisted techniques to explore data, validate metrics, and accelerate insight generation.
• Execute behavioral segmentation based on intent, journey stage, and interaction patterns.
• Synthesize and connect insights across products and user journeys to support enterprise level decision making and prioritization.

• Establish and maintain analytics standards, governance frameworks, and implementation guardrails.
• Document metric definitions, instrumentation patterns, dashboard logic, and reporting…