Marketing Analytics and Data Engineering Lead

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:

1. Educational Background:

Degree in Computer Science, Analytics or Data Science

1. 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)

1. 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

1. Tools and stack

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

The Hertz Corporation operates the Hertz, Dollar Car Rental, Thrifty Car Rental brands in approximately 9,700 corporate and franchisee locations throughout North America, Europe, The Caribbean, Latin America, Africa, the Middle East, Asia, Australia and New Zealand. The Hertz Corporation is one of the largest worldwide airport general use vehicle rental companies, and the Hertz brand is one of the most recognized in the world.