Senior Data Engineer

At Ebury, our ambitious strategic growth plan is powered by data. We are looking for a Senior Data Engineer to join our collaborative Data Engineering team and help build the foundation for data-driven decisions across the entire business. Our Data team, comprising Data Scientists, Data Engineers, Analytics Engineers, and Data Analysts, is on a mission to build, scale, and maintain a world-class Data Platform.

Responsibilities

Build & Orchestrate: Design, deploy, and maintain robust ELT/ETL data pipelines from diverse sources (transactional databases, REST APIs, and file-based endpoints); Model & Warehouse: Collaborate on scalable data models to supply clean, structured data for BI tools and department-specific decision-making; Modernize & Optimize: Manage orchestration using Apache Airflow (GCP Cloud Composer) and leverage GCP native services (Cloud Run, GKE, Cloud Functions, Artifact Registry); Drive Engineering Excellence: Apply software engineering best practices (version control, CI/CD, testing, code reviews) while actively reducing technical debt; Automate & Empower: Automate end-to-end data workflows to eliminate manual extracts, freeing teams across Ebury to focus on high-value analysis; Govern & Refine: Help implement data quality standards, access controls, and data governance policies across the platform

Requirements

3+ years in data engineering, with a track record of building, maintaining, and optimizing pipelines in big data environments; Strong proficiency in Python and SQL; Solid understanding of SDLC, testing, documentation (RFCs), and continuous deployment in a data environment; A strong curiosity to stay up to date with modern data industry standards, technologies, and best practices; Professional fluency in English

Nice to have

Hands-on experience with key tools in our stack (dbt, GCP, Airflow, Looker); Strong grounding in dimensional modeling and data warehousing concepts

Benefits

Tailored Onboarding: A personalized 30/60/90-day plan with 1:1 mentorship from an experienced team member; High-Impact Work: Direct influence over platform architecture, data governance, and core business decisions; Collaborative Culture: A supportive environment where data modeling reviews, knowledge sharing, and best practices are actively encouraged