Senior Engineering Lead - Identities and Attributes

Job description

We are looking for a highly accomplished Senior Engineering Lead to take the helm of one of our core teams within the Identity Risk Platform squad. This is a critical, high‑impact leadership role where you will simultaneously drive architectural strategy and scale the team responsible for Wise’s core identity layer, the foundation on which all risk, onboarding, and servicing decisions are built, powering Wise’s global risk platforms and customer experience.

Key leadership focus

• Architectural ownership You will be the technical authority for the design, delivery, and operational excellence of our core Identity and Attribute domains and related APIs – high‑throughput, low‑latency services that are the backbone of the Identity Risk Platform, and power all product and risk teams.
• Domain bridge You will operate as the primary technical interface between Product squads, Risk/FinCrime, and Verification providers, ensuring clean, reusable API contracts and a unified identity view.
• Team foundation & growth You’ll be instrumental in hiring, mentoring, and leading a multi‑level engineering team, setting the standards and practices that become the foundation for the whole Identity Risk Platform.

Data Integrity & Scale

• You’ll own schemas and data contracts for people, businesses, roles and attributes, and drive data quality, lineage, and auditability so that identity data is trustworthy, explainable, and compliant across its full lifecycle. What will you be working on?

As Senior Engineering Lead for the Identities and Attributes team, your focus will span technical strategy, architectural execution, and team leadership within a high‑stakes, cross‑functional domain.

Evolution of our Identity domains

Leading the design and evolution of our core Identity and Attributes domains. This involves defining robust API contracts and data schemas, making identity data risk‑aware by design, managing attribute acquisition & lifecycle, powering new onboarding & product experiences.

Driving Data Governance

Establishing and enforcing technical standards for Data Lineage, Data Quality, and Auditability within the Identity Risk Platform. You'll ensure the platform meets stringent regulatory and compliance requirements.

Scaling the Team and Culture

Actively managing and mentoring the current engineering team (IC2-IC4), while driving the recruitment strategy to grow the team. This includes defining clear roles, efficient processes, and a high-performance engineering culture.

Strategic Stakeholder Alignment

Serving as the key technical partner to Product, FinCrime, and other Engineering Leads.

You will champion the architectural vision for the platform, ensuring technical decisions align with both business agility and security requirements.

Platform Resilience

Ensuring the platform is built for high availability, low latency, and massive scale, managing the operational health (SLAs/SLOs) of a critical, real-time risk service.

Qualifications

A bit about you

You have strong, hands-on technical experience in OOP Languages ( Java ) and modern technology stacks on technologies such as REST APIs, microservices, distributed systems and CI/CD pipelines - you will have to complete technical interviews to showcase your knowledge . You have proven experience in leading and mentoring software engineers. You have a strong product and customer mindset and experience building customer facing products.

You have experience working with and building distributed, high scalability systems and microservices architectures You're a great communicator who can articulate complex technical concepts clearly to both technical and non-technical audiences. You thrive in a collaborative environment and have experience working effectively with cross-functional peers like designers, product managers, analysts and data scientists. Expert in schema design, indexing strategies, and query optimization for ACID-compliant transactional data.

Experience with partitioning and read-replicas for scaling. Handling unstructured data at scale, implementing sharding, and optimizing aggregation pipelines for high-speed reads/writes and flexible schema evolution. Leveraging Redis or Valkey for high-performance distributed caching