Data Engineer, Security Analytics

Job description

Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. DATA ENGINEER 🔐 About our Security Team As Wayve’s security program grows, we need a scalable way to measure control effectiveness, automate evidence collection and provide continuous visibility into our security posture. As a Data Engineer, you’ll join the Security team and build the data and automation capabilities that underpin our security program. You’ll work across Security to design scalable data pipelines, data models, integrations and automations that transform security data into actionable insights. Your work will improve operational decision-making, reduce manual effort and strengthen our ability to support customer, auditor and regulatory commitments. This is an opportunity to build Wayve’s security analytics capability from the ground up, defining the architecture, data models and automations that become the foundation for how we measure and improve security. 🧠 Your day-to-day You’ll help make security governance continuous by partnering with Security Engineering, IT and Engineering teams to automate evidence collection, measure control effectiveness and establish the foundations of a data-driven security program. You’ll build and maintain security data pipelines, integrate information from cloud, identity, engineering and security platforms, and develop analytics and visualisations that make our security posture easier to understand and act on. You’ll also identify opportunities to replace repetitive manual processes with scalable engineering solutions. This role is well suited to someone motivated by automation who believes security data should be continuously available, reliable and actionable. 🧩 What you’ll be working on: - Designing, building and maintaining scalable data pipelines that collect, transform and enrich security data from systems across Wayve. - Integrating data from identity, cloud, engineering and security platforms to create a unified view of Wayve’s security posture. - Building robust data models that provide high-fidelity datasets for security analytics, operational reporting and measuring control effectiveness. - Designing analytics products and visualisations that provide meaningful insights into the health, maturity and performance of the security program. - Ensuring data quality, lineage, reliability, observability and maintainability across our security analytics platform. - Building automated evidence-collection capabilities that reduce manual effort across governance, customer assurance and security operations. - Developing analytics that support continuous control monitoring and demonstrate control effectiveness through measurable outcomes. - Partnering with stakeholders across Security to translate security controls into measurable, automated indicators where practical. - Designing and implementing automations that replace repetitive operational processes with scalable engineering solutions. - Partnering with subject-matter experts to develop meaningful KPIs and metrics that help Security understand performance, risk, trends and operational health. - Working with stakeholders across Security to understand analytical requirements and translate them into scalable technical solutions. - Continuously improving how security data is collected, modeled and consumed across the organization. During your first year, you’ll establish the foundations of Wayve’s security analytics and automation capability, including continuous security data pipelines, automated evidence collection for selected key controls, meaningful security KPIs and reusable data products. Your work will help move the Security program from periodic assessment toward continuous measurement and assurance. 🙌 You should apply if: - You have experience designing and operating reliable data platforms or analytics engineering solutions in production environments. - You have experience building production-quality data pipelines and automation using Python, SQL or similar technologies. - You have experience modeling data for analytical use cases. - You have a strong understanding of modern data engineering practices, including data modeling, ETL/ELT, API integrations, data quality and observability. - You have experience working in cloud-native environments and integrating data from cloud platforms and SaaS sources. - You have experience building integrations and automation using APIs rather than relying solely on out-of-the-box platform capabilities. - You bring strong analytical and problem-solving skills and can translate complex technical data into actionable insights. - You have experience designing dashboards and metrics that sup