Senior Analytics Engineer - Treasury & Exposure Management

Location: Madrid/Malaga (Hybrid: 4 days office / 1 day WFH)

You will be embedded within our Treasury& Exposure domain, ebury's operates under a Domain-Driven Design (DDD) model where data and product engineering align to build true data products. 

This is a great opportunity for someone who wants to move beyond "just coding." You will be fully involved in the domain, sitting at the intersection of Product, Tech, and Data to understand and drive the business impact of every model you build. In the AI era, business context is no longer optional; we need an engineer who speaks both "data" and "finance".

What you will do:

• Partner with the business to gather requirements and define technical action plans for robust data products.
• Lead projects from initial definition to delivery, including strategies for stakeholder (impact and testing)
• Ability to split between strategic management and technical execution; you are equally comfortable architecting a multi-domain roadmap as you are diving into the IDE to ship a critical fix
•  Proactively monitor and govern data products to ensure high reliability. You will design and propose ongoing alerting frameworks to catch anomalies before they reach the business.
• Deliver hands-on data models using modern software engineering practices (version control, testing, and CI/CD).
• Collaborate with team members to reinforce best practices across the platform, encouraging a shared commitment to quality.
• Manage overall pipeline orchestration using Airflow (hosted in Cloud Composer).
• Contribute to and promote best practices for query development, version control, code review, documentation, and testing

What we're looking for:

• 4+ years experience in similar roles, solid analytics engineering background - dbt, SQL, data modeling, and a strong sense of what makes a data product trustworthy and maintainable.
• High proficiency in SQL with the ability to build, robustly test, and optimize complex models.
• A strong sense of what makes a data product trustworthy, maintainable, and valuable to the end user.
• Finance domain knowledge, you understand how financial data works: P&L, FX, exposure, reconciliation.
• Experience with (or a genuine curiosity for) Domain-Driven Design and how it shapes team ownership and data structure.
• Fluency in English (Spanish is a plus).