Engineering Lead - Comparison Team (Data Focused)

We are looking for a talented Engineering Lead to join our Comparison team, part of the Onboarding & Scalable Growth squad

Comparison is about transparency, helping customers understand the real cost of sending money and why Wise is the better choice. You'll own the systems that collect pricing data from competitors and make it accessible across Wise. That data serves two customers: customer-facing comparison experiences (web pages, widget, calculator and the public API), and competitive intelligence that helps Marketing, Regional and Pricing teams shape their strategy.

This means creating the underlying technology that enables Wise to build intelligent and resilient (self-healing) scrapers at scale (thousands) operating with minimal manual intervention. It also includes building reliable data pipelines, and APIs that teams depend on. Accuracy and trust are non-negotiable.

The comparison team is small but growing: full-stack and backend engineers working with Product, Analytics, Design and Comparison Operations. The work covers the whole stack, from data collection pipelines and backend services to the React/Next.js experiences customers see. We're looking for a lead who is comfortable on both sides and is excited by data-heavy products and is driven to build a scalable and reliable data collection framework.

• Lead, coach and mentor the engineers in your team. You'll own their health, growth and productivity, and grow the team as it scales.

• Work closely with the Product Manager to shape the roadmap and technical vision across our three growth levers: reach (collect pricing in new markets and new products), convert (enhance our comparison web pages, widget and calculator) and retain (introduce comparison in the logged-in experience).

• Own the reliability, accuracy and scalability of our competitor data platform and the public Comparison API, from collection and validation through to how the data is served.

• Own the technical strategy and delivery of our intelligent scraping platform. Architect and scale the core technology that empowers teams to deploy thousands of intelligent, self-healing, and resilient scrapers, minimizing manual maintenance while maximizing data accuracy.

• Push forward how we use AI in our data pipeline, for example LLM scrapers, automated quality control and AI-assisted ways to fix scrapers. Make sure we adopt it safely, measurably and at scale.

• Give feedback on technical designs and help the team make data-driven decisions, using experiments and our North Star metric (Comparison-sourced new customers) to decide what to build next.

• Partner across Wise, including Marketing, Compliance, SEO, Regional, and Pricing teams, to establish clear operating models, request triage, and governance so that comparison data is trusted wherever price proof matters, while balancing customer-facing and internal user needs with clear trade-offs.

• Keep an overview of the wider Scalable Growth space and think about engineering as a whole, including how other teams can build on our data and tooling.

• Understand the team's systems deeply enough to be hands-on when needed, and join the team's on-call rotation for our critical services.

We are fully aware that it is uncommon for a candidate to have all skills required and we fully support everyone in learning new skills with us. So if you have some of those listed below and are eager to learn more we do want to hear from you!

• A track record of leading, coaching and mentoring driven, high-performing teams. Experience setting up ways of working that help a team deliver fast while improving reliability and quality.

• A strong product mindset and a passion for UX. You prioritise work with customers in mind and make data-driven decisions to fix customer pain points

• Great communication skills and the ability to explain complex technical concepts to non-technical audiences

• Experience designing and operating scalable, resilient systems that handle large amounts of data and traffic, with a focus on observability, data quality. You can demonstrate how you reduced manual operational work while maintaining reliability and correctness

• The ability to break down complex projects into incremental milestones that deliver customer value, especially when you're entering a new product area or market

• Knowledge of and experience with Java and Spring Boot, event-driven microservices architectures (for example Kafka) and relational databases

• Experience with, or a strong interest in, applying LLMs in production: data extraction, evaluation and observability, and guarding against hallucination

• Hands-on experience designing and operating systems that collect and validate data from changing or unreliable external sources (e.g. web scraping, third-party integrations).

• Experience running experiments (A/B testing) and working closely with analysts is a plus