About Moneybox   At Moneybox, our mission is to give everyone the means to get more out of life. We're guided by our belief that wealth isn't about the money, it's about the means to more - more freedom, opportunities, possibilities, and peace of mind. Moneybox is an award-winning wealth management platform, helping over one and a half million people build wealth throughout their lives, whether they’re saving and investing, buying their first home, or planning for retirement.   Job Brief

We're looking for a senior Marketing Insight & Analytics Lead to join the Data & Insight team on a fixed-term basis. This role is dedicated to supporting our Marketing function, acting as the analytical and technical centre of gravity for everything from campaign measurement to martech data infrastructure.

Working closely with Marketing, Analytics Engineering, Data Engineering and Product Engineering, you'll translate the findings of our ongoing MarTech audit into clear data and measurement requirements, helping shape the technical foundations of a more sophisticated marketing analytics ecosystem.

What You'll Do

Marketing Tracking & Measurement Architecture
• Assess and improve marketing tracking across paid, owned and earned channels, identifying gaps in campaign tagging, event instrumentation, attribution and measurement coverage.
• Define standards for campaign taxonomy, tracking parameters, event definitions and marketing measurement consistency across platforms.
• Lead the definition of end-to-end web-to-app measurement requirements, ensuring customer journeys can be understood across acquisition, registration, onboarding and downstream product engagement.
• Bring deep expertise in platforms such as Google Analytics 4, AppsFlyer and relevant advertising and product analytics tools to define how tracking should be implemented, validated and maintained.
• Establish clear measurement specifications, technical requirements and acceptance criteria for engineering delivery.
Customer Journey Measurement & Technical Delivery
• Work with engineering teams to establish appropriate approaches for anonymous-to-known identity stitching, attribution identifiers, event mapping and cross-platform journey continuity, within applicable privacy and consent constraints.
• Identify limitations in existing attribution data and recommend practical improvements.
• Partner with relevant stakeholders to translate business needs into a prioritised marketing analytics and data development roadmap.
• Act as the primary owner of marketing analytics requirements for Analytics Engineering, Data Engineering and Product Engineering.
• Define the data sources, integrations, event specifications, transformation requirements and data products needed to deliver improved marketing measurement.
• Work closely with engineering teams to shape technical solutions, manage dependencies and validate that delivered capabilities meet business and measurement requirements.
• Establish appropriate data quality, reconciliation and monitoring requirements for marketing data flows and tracking implementations.
Data Products & Reporting
•  Define and document sources of truth for key marketing KPIs, ensuring consistency across reporting surfaces
• Own the marketing reporting layer in Power BI (or equivalent), ensuring outputs are accurate, timely, and interpretable by non-technical audiences
• Leverage AI to automate routine reporting, draft performance narratives, and surface key trends or anomalies
Stakeholder Partnership
• Serve as the primary data and analytics partner for the Marketing team, translating commercial questions into analytical briefs and technical requirements
• Support media planning cycles with data-driven audience segmentation, channel mix analysis, and budget allocation modelling
•  Represent the Data & Insight team in cross-functional marketing planning forums, contributing to roadmap prioritisation

Who You Are

• A technically strong marketing analytics professional who understands how digital marketing data is generated, tracked, connected and measured.
• Comfortable operating between Marketing and Engineering, translating commercial measurement needs into detailed technical requirements.
• Experienced in solving complex attribution, tracking and identity challenges across web and mobile environments.
• Able to assess existing measurement architecture, identify weaknesses and propose practical, scalable improvements.
• Commercially minded, with a clear understanding of how marketing effectiveness, acquisition efficiency and customer value influence investment decisions.
• Confidence in challenging existing approaches and making informed recommendations when data quality or measurement limitations prevent reliable conclusions.

Experience & Skills

Essential

• 5+ years in a marketing analytics, data science, or analytics engineering role with a strong focus on marketing measurement
• Hands-on experience with multi-touch attribution methodologies and media mix modelling
• Strong SQL skills; experience using it for data manipulation, data analysis, and modelling
• Direct experience with mobile attribution platforms, particularly AppsFlyer
• Familiarity with the privacy landscape across both app (e.g. iOS SKAdNetwork) and web (e.g. cookie deprecation), and how to navigate the resulting measurement challenges
• Experience working with advertising platform APIs (Google Ads, Meta Ads) for data extraction and pipeline automation
• Familiarity with GCP data services and event analytics platforms (Mixpanel or equivalent)
• Demonstrable experience building data products and self-serve reporting assets used by non-technical stakeholders
• Track record of designing and analysing incrementality experiments or A/B tests in a marketing context

Desirable

• Experience with dbt (Cloud or Core) for transformation layer development
• Familiarity with Databricks or similar modern data lakehouse platforms
• Experience with Power BI (or similar data visualisation tool)
• Experience in a regulated financial services or fintech environment
• Exposure to customer data platforms (CDPs) or CRM data integration (e.g. Braze)
• Experience working within or alongside analytics engineering teams and contributing to shared data models
• Understanding of CI/CD practices for data pipelines
• Experience with Python for data manipulation, modelling, and pipeline work

Whats In It For You

• Join a fast-growing, award-winning company with genuine ambition to improve people's financial lives
• Work in a team that takes data quality and analytical rigour seriously, with a modern stack and strong engineering culture
• Dedicated, focused remit – you'll be the subject matter expert in your domain, with real ownership and visibility
• Hybrid working: 2 days from our London office, 3 from home
• Competitive FTC compensation package