Head of Analytics Engineering

What do we do? Paddle offers digital product companies a completely different approach to their payment infrastructure. Instead of assembling and maintaining a complex stack of payments-related apps and services, we’re a Merchant of Record for our customers. That means we take away 100% of the pain of payment fragmentation. It’s faster, safer, cheaper, and, above all, way better. We’re backed by investors including KKR, FTV Capital, Kindred, Notion, and 83North and serve over 5000 software sellers in 245 territories globally. The role: As an Analytics Engineering Manager, you'll lead a dynamic team, working closely with various business units to translate complex business requirements into actionable data solutions. You will play a critical role in communicating analytics insights clearly and with impact, enabling data-driven decision-making across the organization. Collaboration with Sales, Marketing, Finance, Product Managers, and Engineering teams will be essential to align analytics solutions seamlessly with business objectives and technical capabilities. What you'll do: Leadership & Strategy - Define and own the multi-year technical vision and strategy for Analytics Engineering, ensuring alignment with Paddle's product and business objectives. - Lead, coach, and develop a team of Senior Analytics Engineers, fostering a high-performing, inclusive, and growth-oriented culture. - Act as a force multiplier across the group: identifying and removing structural blockers, elevating engineering standards, and scaling delivery capacity. - Drive and champion best practices in analytics engineering, data modelling, data governance, and operational excellence across all teams. Stakeholder Management - Serve as the senior Engineering representative for Analytics Engineering with cross-functional leaders in Product, Finance, Sales, Marketing, and Data Platform. - Build and maintain trusted, long-term relationships with stakeholders at Director and VP level, proactively aligning on goals, managing expectations, and communicating progress and risk with clarity and transparency. - Navigate competing priorities across multiple senior stakeholders; make and communicate clear, well-reasoned trade-off decisions that reflect both engineering and business considerations. - Represent Analytics Engineering in Engineering leadership forums and contribute to shaping the broader engineering organisation. - Advocate effectively for investment (headcount, tooling, infrastructure) by constructing well-evidenced business cases and presenting them to senior leadership. Data as a Product - Champion a product mindset for data across the organisation: ensuring Paddle's analytics data estate is treated as a first-class product with clear ownership, defined consumers, and measurable quality standards. - Lead the definition and governance of shared data definitions and business metrics, working cross-functionally to drive alignment and eliminate ambiguity across teams. - Ensure all data assets are well documented, well understood, and readily discoverable, including via MCP tooling, so that engineers, analysts, and business stakeholders can self-serve with confidence. - Define and enforce clear data ownership across the analytics estate, ensuring every dataset and model has an accountable team and a well-understood purpose. - Establish and continuously improve data quality standards: defining what "good" looks like, instrumenting quality checks throughout the pipeline, and ensuring issues are surfaced, triaged, and resolved systematically. - Own the prioritisation of the Analytics Engineering roadmap, balancing strategic data product initiatives, platform reliability, data quality improvements, and stakeholder requests in a structured and transparent way. - Build and maintain the processes by which new data needs are brought into engineering, evaluated, and sequenced, ensuring the group can absorb demand predictably and say no clearly when needed. Technical Ov