Ebury is a hyper-growth FinTech firm, named 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.
Senior Data Engineer - Data Platform Engineering Location: Madrid Office - Hybrid: 4 days in the office, 1 day working from home Join 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 Senior Data Engineer to join our Data Platform Engineering team!
Our data mission is to develop and maintain Ebury's Data Warehouse 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 platform.
Provide clean, transformed data ready for analysis and used by our BI tool.
Develop department and project-specific data models to drive decision making.
Automate end solutions to focus on high-value analysis rather than running data extracts.
We are looking for a skilled Senior Data Engineer with a strong focus on building and optimising data platforms.
In this role, you will be responsible for developing, enhancing, and maintaining robust frameworks and best practices to support our analytics and ML initiatives.
You will work closely with data analysts and other engineering teams to ensure our data platform is scalable, secure, and efficient.
Why should you join Ebury?
We are always growing in a high-growth environment.
We believe in inclusion and stand against discrimination in all forms.
At Ebury, you will find an internal group dedicated to discussing how we can build a more diverse and inclusive workplace for all people in the Technology Team.
If you're excited about this job opportunity but your background doesn't match exactly the requirements, we strongly encourage you to apply anyway.
About our technology and Data stack: We use: Google Cloud Platform as our main Cloud provider Apache Airflow as orchestration tool Docker as PaaS to deliver software in containers dbt for data transformation Looker and Looker Studio as BI tools Github as code management tool Jira as project management tool Synq as a data observability tool Among others third party tools such as: Hevodata, MonteCarlo, Synq What we offer: Variety of meaningful and competitive benefits to meet your needs: Competitive salary Continuous professional growth through our career progression framework with regular reviews Equity process through a performance bonus Annual paid time off and local public holidays Continued personal development through training and certification Being part of a diverse technology team that cares deeply about culture and best practices We are Open Source friendly, following Open Source principles in our internal projects and encouraging contributions to external projects Responsibilities: Establish performance monitoring to track the speed and efficiency of data processing and analysis, and address bottlenecks or slowdowns as needed.
Participate in data modelling reviews and discussions to validate the model's accuracy, completeness, and alignment with business objectives.
Work on reducing technical debt by addressing outdated or inefficient code.
Help implement data governance policies, including data quality standards and data access control.
Collaborate with data scientists, analysts, and stakeholders to understand data requirements and translate them into platform capabilities.
Automate data ingestion, transformation, testing, and integration processes to enhance data accessibility and quality.
Evaluate and integrate new data tools and technologies to continuously improve the platform's capabilities.
Create and maintain detailed documentation on platform architecture, data flows, and operational processes.
Collaborate with team members to reinforce best practices across the platform.
Experience and qualifications: 3+ years of experience as a Data Engineer or in a similar role.
Proficiency in SQL and Python.
Experience with modern data stack tools (a plus).
Familiarity with dimensional modelling/data warehousing concepts.
Basic understanding of data governance practices.
Experience with software engineering practices in data.
Attention to detail and commitment to data quality.
Fluency in English (Spanish, a plus).
Even if you don't meet every requirement listed, we encourage you to apply—your skills and experience might be a great fit for this role or future opportunities!
We welcome applications from candidates who require a work permit.
For non-EU/EEA nationals, the company may assist with the work permit process, depending on individual circumstances.
About Us Ebury is a FinTech success story, positioned among the fastest-growing international companies in its sector.
Founded in [year], we are headquartered in London and have more than [number] staff with a presence in more than 25 countries worldwide.
Cultural diversity is part of what makes Ebury a special place to be.
Hard work pays off: in [year], Ebury received a £350 million investment from Banco Santander and has won internationally recognised awards including Financial Times: Europe's Fastest-Growing Companies.
None of this would have been possible without our great people.
We believe in inclusion and stand against discrimination in all forms.
Please submit your application on the careers website directly, uploading your CV/resume in English.
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