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 rules
- Platform integrations: Build robust connectors/APIs for GA4, GMP (CM360/DV360/SA360), Meta and other platforms. Unify with Databricks, COGNOS and Salesforce
- Data engineering: Model clean tables/views, implement data quality checks and documentation
- Dashboards and reporting: Deliver looker studio and Tableau dashboards, automate recurring reporting, provide training to channel owners
- Attribution and MMM: Deploy open source MMM (Meta Robyn, Google Meridian), design holdouts, support hybrid attribution and incrementality studies
- Governance and compliance: Ensure GDPR/Consent compliance, maintain audit trails, partner with legal on risk mitigation
- Troubleshooting and enablement: Act as a single point of contact for data/tracking issues, triage quickly, run enablement sessions and documentation
Key KPIs
- Tag coverage rate and accuracy; reduced data discrepancy between platforms and data sources
- Pipeline uptime and latency SLAs; time to lag and time to insight reductions
- Dashboard adoption and stakeholder satisfaction
- Evidence based budget reallocation % driven by MMM/holdouts; lift from incrementality tests
- Compliance readiness; consent coverage, audit trail completeness
- Profile and Experience:
Educational Background:
- Degree in Computer Science, Analytics or Data Science
Professional Experience:
- 5-8 years in analytics/data engineering or marketing analytics engineering roles
- Expertise in GTM/GA4/GMP/Meta tracking; strong SQL, experience with BigQuery or equivalent
- Hands on APIs
- Proficiency 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 competencies
- Structured problem solving, bias to automate and standardise
- Clear communicator who can translate between technical and commercial stakeholders
- Strong ownership and prioritisation; able to manage technical backlog and SLAs
- Documentation discipline; enablement mindset to upskill the wider team
Tools and stack
- BigQuery, Python/R, GA4, CM360/DV360/SA360, Meta
- Looker Studio/Tableau, Serverside GTM, privacy and consent platforms
- Salesforce, COGNOS, Databricks
What You’ll Get:
- Up to 40% off any standard Hertz Rental in a Corporate country
- Paid Time Off
- Employee Assistance Programme for employees and family
