Ebury
SeniorAnalyticsEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Analytics Engineer at Ebury. Skills: Analytics engineering, Data modeling, SQL. Partner with business to gather requirements. Define technical action plans”
Industry & Context.
Problem-solving
What They're Looking For.
Must Have
4+ years experience, Solid analytics engineering background, High proficiency in SQL, Finance domain knowledge, Fluency in English
Nice to Have
Spanish is a plus, Curiosity for Domain-Driven Design
What You'll Do.
Partner with business to gather requirements
Define technical action plans
Lead projects from definition to delivery
Monitor and govern data products
Design and propose alerting frameworks
Deliver hands-on data models
Collaborate with team members
Manage pipeline orchestration
Contribute to best practices for query development
Promote best practices for version control
Promote best practices for code review
Promote best practices for documentation
Promote best practices for testing
How You'll Work.
Team & Collaboration
Product, Engineering, and Data align; Collaborate with team members
Process & Methodology
Stakeholder management, Strategic management
Full Job Description
Ebury helps ambitious businesses unlock global growth, and we take the same approach with our people. We encourage innovation and movement, collaboration and problem-solving, and foster an environment where everyone can feel they belong, are valued, supported and empowered to succeed. If you’re a collaborator who wants to help transform how businesses operate globally, get in touch - we’d love to discuss how Ebury can accelerate your career so you can shape the future. Senior Analytics Engineer Location: Madrid (Hybrid: 4 days office / 1 day WFH) We are looking for an Analytics Engineer to be embedded within one of our core product domains. You will be the owner of your domain's data warehouse, responsible for setting the standards, patterns, and practices that govern how data is modelled, structured, and consumed within your domain. You will build the semantic layer that provides the context, definitions, and structure necessary for AI agents and business stakeholders to leverage data effectively — turning raw domain data into trusted, reusable assets that the wider organisation can depend on. We operate under a Domain-Driven Design (DDD) approach, where Product, Engineering, and Data align on shared goals to eliminate bottlenecks and ensure architectural coherence across the organisation. 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 c
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