.Ebury is a hyper-growth FinTech firm, named in 2021 as one of the top 15 European Fintechs to work for by AltFi. We offer a range of products including FX risk management, trade finance, currency accounts, international payments and API integration.Data Engineer - FintechMadrid Office - Hybrid: 4 days in the office, 1 day working from homeJoin Our Technology Team at Ebury Madrid Office.Ebury's strategic growth plan would not be possible without our Data team and we are seeking a Data Engineer to join our Data Engineering team!Our data mission is to develop and maintain Ebury's Data Platform and serve it to the whole company, where Data Scientists, Data Engineers, Analytics Engineers and Data Analysts work collaboratively to:Build ETLs and data pipelines to serve data in our platformProvide clean, transformed data ready for analysis and used by our BI toolDevelop department and project specific data models and serve these to teams across the company to drive decision makingAutomate end solutions so we can all spend time on high-value analysis rather than running data extractsResponsibilities:Be mentored by one of our outstanding performance team member along a 30/60/90 plan designed only for you.Participate in data modelling reviews and discussions to validate the model's accuracy, completeness, and alignment with business objectives.Design, develop, deploy and maintain ELT/ETL data pipelines from a variety of data sources (transactional databases, REST APIs, file-based endpoints).Serve hands-on delivery of data models using solid software engineering practices (eg. version control, testing, CI/CD)Manage overall pipeline orchestration using Airflow (hosted in Cloud Composer), as well as execution using GCP hosted services such as Container Registry, Artifact Registry, Cloud Run, Cloud Functions, and GKE.Work on reducing technical debt by addressing code that is outdated, inefficient, or no longer aligned with best practices or business needs.Collaborate with team members to reinforce best practices across the platform, encouraging a shared commitment to quality.Help to implement data governance policies, including data quality standards, data access control, and data classification.Identify opportunities to optimise and refine existing processes.Experience and qualifications:3+ years of data/analytics engineering experience building, maintaining & optimising data pipelines & ETL processes on big data environments.Proficiency in Python and SQL.Knowledge of software engineering practices in data (SDLC, RFC...).Stay informed about the latest developments and industry standards in Data.Fluency in English.Experience with our modern Data stack tools is a plus.Dimensional modelling/data warehousing concepts knowledge is a plus.Spanish language is a plus
