Senior Data Engineer - Analytics Platform

<div class="content-intro"><p>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.</p> <p>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.</p></div><p><strong>Senior Data Engineer - Platform&nbsp;</strong></p> <p><strong>Madrid Office - Hybrid: 4 days in the office, 1 day working from home</strong></p> <p><strong>Join Our Data Team at Ebury Valencia office.</strong></p> <p>Ebury's strategic growth plan would not be possible without our Data team and we are seeking a <strong>Senior Data Engineer </strong>to join our <strong>Data Platform Engineering team</strong>! Our mission is to develop, maintain and improve Ebury's Data Platform — this role owns the <strong>Analytics Platform</strong>: the tools, frameworks, and standards that empower our Data Analysts to deliver trusted insights at scale. You will manage the full lifecycle of our BI and visualization stack, built on <strong>Sigma</strong>, together with <strong>dbt</strong> and <strong>BigQuery</strong> as the core modelling and warehousing tools, and help evolve how analysts work — bringing software engineering practices into the analytics workflow.</p> <h3><strong>Responsibilities</strong></h3> <ul> <li>Own and evolve Ebury's analytics platform end-to-end, with <strong>Sigma</strong> as the core BI and visualization tool — administration, governance, versioning, and best practices</li> <li>Define and manage the SDLC for analyst workflows across <strong>dbt</strong> and <strong>BigQuery</strong>: development standards, testing, code review, CI/CD, and release processes</li> <li>Build the frameworks and guardrails that enable <strong>self-service analytics</strong> — ensuring dashboards and datasets are discoverable, documented, governed, and trustworthy</li> <li>Champion metrics consistency across the organisation, ensuring business definitions are aligned between the warehouse, semantic models, and BI layer</li> <li>Support and upskill the Data Analyst community, helping them adopt analytics-engineering practices (version control, testing, modular modelling) as their ways of working evolve</li> <li>Provide observability for analyst-facing data products: usage analytics, freshness, data quality signals, and cost/performance optimisation of BI workloads on BigQuery</li&