Data Engineer
hace 3 meses
Ebury is a hyper-growth FinTech firm, named in 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 - Data Platform EngineerMadrid - 4 days in the office & 1 day working from home About our company:Ebury is a FinTech success story, positioned among the fastest-growing international companies in its sector.
Headquartered in London, we have more than 1, staff covering over 50 nationalities (and counting)
working across more than 27 offices worldwide and serving more than 45, clients every day.About our team: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 teamOur 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 extracts About our technology and Data stack: Google Cloud Platform as our main Cloud providerApache Airflow and dbt Cloud as orchestration toolsDocker as PaaS to deliver software in containersCloud Build as CICDdbt as data modelling and warehousingLooker and Looker Studio as Business Intelligence/dashboardingGithub as code management toolJira as project management tool Among others third party tools such as: Hevodata, MonteCarlo, Synq…About the role:As a Data Engineer, you will work closely with the rest of the team to help model and maintain the Data Platform.
Therefore, we are looking for: At least 3+ years of data/analytics engineering experience building, maintaining & optimising data pipelines & ETL processes on big data environmentsProficiency in Python and SQLKnowledge of software engineering practices in data (SDLC, RFC…)Stay informed about the latest developments and industry standards in DataFluency in EnglishAs a plus: Experience with our modern Data stack toolsDimensional modelling/data warehousing concepts knowledgeSpanish language Why this offer is for you: You will: Be mentored by one of our outstanding performance team member along a 30/60/90 plan designed only for youParticipate 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.
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