At a Glance
- Tasks: Build and optimise marketing data flows for better decision-making and insights.
- Company: Join a forward-thinking company focused on data-driven marketing solutions.
- Benefits: Enjoy paid time off, employee assistance programmes, and a supportive work environment.
- Other info: Collaborative culture with opportunities for professional growth and skill development.
- Why this job: Make a real impact by shaping the future of marketing analytics.
- Qualifications: Degree in Computer Science or related field; experience in analytics or data engineering.
The predicted salary is between 60000 - 80000 € per year.
This role is accountable for establishing greenfield data flows, standards, and operating models, enabling faster, better decision-making through accurate data, integrated views (GA4, Salesforce, Databricks, COGNOS), and scalable insight products (dashboards, attribution, MMM). Act as the primary point of contact for all digital tracking and marketing data issues, ensuring reliability, compliance, and speed across the ecosystem. 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
- Design and build the marketing data foundation from scratch, including tracking architecture, event schemas, identity strategy, and data flows across martech and enterprise platforms.
- 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
- Degree in Computer Science, Analytics or Data Science, 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, Server-side GTM, privacy and consent platforms.
- Salesforce, COGNOS, Databricks.
Benefits
- Paid Time Off.
- Employee Assistance Programme for employees and family.
Marketing Data Analytics Engineer in London employer: The Hertz Corporation
As a Marketing Data Analytics Engineer, you will thrive in a dynamic work environment that champions innovation and collaboration. Our company offers a robust benefits package, including generous paid time off and an Employee Assistance Programme for you and your family, ensuring a healthy work-life balance. With a strong focus on employee growth, we provide opportunities for continuous learning and development, making it an excellent place for those looking to make a meaningful impact in the field of data analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Marketing Data Analytics Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, dashboards, and any cool analytics work you've done. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common questions related to data analytics and marketing. We recommend practising with a friend or using mock interview platforms to build your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Marketing Data Analytics Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Marketing Data Analytics Engineer. Highlight your experience with data flows, tagging standards, and any relevant tools like GA4 or Salesforce. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data analytics and how you can contribute to our team. Don't forget to mention specific projects or achievements that relate to the job description.
Showcase Your Technical Skills:Since this role requires expertise in SQL, APIs, and dashboarding tools, make sure to highlight these skills prominently. We love seeing examples of how you've used these tools in past roles, so feel free to include links to any relevant projects or dashboards you've created.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, it's super easy to do!
How to prepare for a job interview at The Hertz Corporation
✨Know Your Data Tools
Familiarise yourself with the specific tools mentioned in the job description, like GA4, Salesforce, and Databricks. Be ready to discuss how you've used these platforms in past roles, and think of examples where you’ve built data flows or dashboards.
✨Showcase Your Problem-Solving Skills
Prepare to discuss structured problem-solving scenarios from your previous experience. Think about times when you had to troubleshoot data issues or improve tracking standards, and be ready to explain your thought process clearly.
✨Communicate Clearly
Since this role involves translating technical details to commercial stakeholders, practice explaining complex concepts in simple terms. You might want to prepare a few examples where you successfully communicated data insights to non-technical team members.
✨Demonstrate Your Ownership Mindset
Be prepared to talk about how you prioritise tasks and manage backlogs. Share examples of how you’ve taken ownership of projects, especially those involving data governance or compliance, and how you ensured timely delivery.
