MarTech Lead

Who you are

• You're a technologist first, not a project coordinator. Someone who's more comfortable in a SQL console or a data pipeline than in a status meeting, and who reaches for AI tools instinctively to move faster rather than waiting for someone else to build the tool for you
• You are comfortable operating in ambiguity, able to connect the dots between teams and skilled at turning broad goals into practical technical plans. You understand how marketing technology, measurement and data work together at a hands-on level, not just conceptually
• Strong ability to translate business objectives into structured delivery plans, requirements and documentation
• Clear, confident communication skills with the ability to work effectively across teams with different priorities, disciplines and levels of technical understanding
• Experience managing multiple initiatives in parallel, including coordination of external vendors and delivery partners, while maintaining focus on outcomes
• Strong SQL and comfort working in BigQuery or an equivalent warehouse. You can write your own validation queries, not just request them
• Working proficiency in Python (or another mainstream language) for scripting data checks, automation, and pipeline debugging
• Practical experience building with AI/LLM tools. Automating a workflow, building an internal agent, or similar beyond casual chatbot use
• Experience owning (not just contributing to) at least one platform migration or major data integration project
• Comfort designing data architecture, schema decisions, identity resolution, reconciling conflicting data across systems

What the job involves

• Our MarTech team is evolving as we take on projects that will reshape how we communicate with clients, personalise their experiences, improve marketing performance and embed AI into how our marketing teams work. As MarTech Lead, you will drive the successful delivery of a complex and evolving marketing technology roadmap spanning customer engagement, data infrastructure, performance marketing measurement and AI enablement
• We're looking for a hands-on MarTech Lead to take technical ownership of our marketing technology stack, not just manage the roadmap, but get into the data and fix what's broken
• You'll lead two flagship projects: building a single source of truth by integrating and reconciling data across 40+ tools (Braze, GA4/BigQuery, Salesforce, and more) and owning our SFMC (Salesforce Marketing Cloud) to Braze migration end-to-end, including data validation and technical sign-off
• Day to day, you'll diagnose data quality issues directly and use AI tooling to automate the manual work that used to take a whole team
• This is a technical role at heart, strong data engineering fundamentals and real fluency with AI-assisted workflows matter more here than project management polish
• Act as the technical owner of the SFMC → Braze migration: own the plan, sequencing, and cutover strategy, not just a workstream within it
• Personally validate data and journey parity between SFMC and Braze, reconciling records, logic, and event data at the SQL/pipeline level, not just sign-off via a status report
• Identify and fix migration-related data issues directly (mapping errors, duplicate/missing events, broken triggers) rather than logging tickets for someone else to resolve
• Own the technical relationship with Client Tech and Data Architecture for everything migration-related, uptime, data integrity, and rollback/contingency planning
• Define the technical architecture for a unique source of truth, schema design, identity resolution/stitching across tools, update cadence, and ownership of conflicts when tools disagree
• Manage integrations of 3rd-party tools, understanding the technical data contracts involved, spec how data from disparate tools should be integrated, deduplicated, and reconciled into a single, trusted data store
• Work with Data Architecture and the data warehouse team to align this with the existing BigQuery/attribution setup
• Build validation/monitoring so the source of truth is trusted by default, flag drift or breakage before stakeholders notice bad numbers
• Diagnose and resolve data quality issues directly. Duplicate events, integer overflow/ID issues, broken field mappings, integration failures rather than escalating to a data engineer
• Write and maintain SQL/Python for data validation, QA scripts, and user journey debugging
• Use AI tools (LLM-based agents, scripting, internal automation) to speed up recurring MarTech work: QA checks, documentation, campaign audits, migration validation, training material generation etc
• Manage vendor relationships