Design, build and govern marketing data foundation – tagging, tracking, pipelines and modelling to create a single source of truth across brand direct, paid, social and CRM. Enable faster, better decisions with accurate data, integrated views (GA4, Salesforce, Databricks, COGNOS) and insight products (dashboards, attribution/MMM). Be the primary point of contact for all tracking and data issues ensuring reliability, compliance and speed.Own tagging and tracking standards for web/app (GTM, GA4, CM360/Floodlight, Meta pixel/event manager, consent mode) Define and maintain the marketing KPI dictionary and data model; steward the single source of truth. Define data pipelines between martech platforms and enterprise solutions (Salesforce, COGNOS, Databricks). Set QA/alerting SLAs, prioritise analytics backlog. Advise on experimentation, attribution and MMM, recommend budget reallocations based on evidence.Key Responsibilities:Tagging and implementation: Deploy and audit events, conversions, and consent, server-side GTM evaluation, manage parameter standards and de-duplication rulesPlatform integrations: Build robust connectors/APIs for GA4, GMP (CM360/DV360/SA360), Meta and other platforms. Unify with Databricks, COGNOS and SalesforceData engineering: Model clean tables/views, implement data quality checks and documentationDashboards and reporting: Deliver looker studio and Tableau dashboards, automate recurring reporting, provide training to channel ownersAttribution and MMM: Deploy open source MMM (Meta Robyn, Google Meridian), design holdouts, support hybrid attribution and incrementality studiesGovernance and compliance: Ensure GDPR/Consent compliance, maintain audit trails, partner with legal on risk mitigationTroubleshooting and enablement: Act as a single point of contact for data/tracking issues, triage quickly, run enablement sessions and documentationKey KPIsTag coverage rate and accuracy; reduced data discrepancy between platforms and data sourcesPipeline uptime and latency SLAs; time to lag and time to insight reductionsDashboard adoption and stakeholder satisfactionEvidence based budget reallocation % driven by MMM/holdouts; lift from incrementality testsCompliance readiness; consent coverage, audit trail completenessProfile and Experience:Educational Background:Degree in Computer Science, Analytics or Data ScienceProfessional Experience: 5-8 years in analytics/data engineering or marketing analytics engineering rolesExpertise in GTM/GA4/GMP/Meta tracking; strong SQL, experience with BigQuery or equivalentHands on APIsProficiency with dashboarding (Looker studio/Tableau) and at least one scripting language (Python or R)MMM/Attribution exposure (Robyn, Meridian) and understanding of privacy frameworks (GDPR. Consent mode)Skills and competenciesStructured problem solving, bias to automate and standardiseClear communicator who can translate between technical and commercial stakeholdersStrong ownership and prioritisation; able to manage technical backlog and SLAsDocumentation discipline; enablement mindset to upskill the wider teamTools and stackBigQuery, Python/R, GA4, CM360/DV360/SA360, MetaLooker Studio/Tableau, Serverside GTM, privacy and consent platformsSalesforce, COGNOS, DatabricksWhat You’ll Get:Up to 40% off any standard Hertz Rental in a Corporate countryPaid Time OffEmployee Assistance Programme for employees and family