Senior Data Engineer
hace 2 semanas
About the Role
Ebury is a fast-growing FinTech firm that offers a range of products including FX risk management, trade finance, currency accounts, international payments, and API integration. As a Senior Data Engineer, you will be part of our Data Platform Engineering team, responsible for developing and maintaining Ebury's Data Warehouse.
About the Team
Our data mission is to develop and maintain Ebury's Data Warehouse, serving 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 and serve these to teams across the company to drive decision-making
- Automate end solutions so we can all spend time on high-value analysis rather than running data extracts
About You
We are looking for a skilled Senior Data Engineer with a strong focus on building and optimizing data platforms. You will have 3+ years of experience as a Data Engineer or in a similar role, proficiency in SQL and Python, and experience with our modern data stack tools. Familiarity with dimensional modeling/data warehousing concepts and basic understanding of data governance practices are also required.
About Ebury
Ebury is a FinTech success story, positioned among the fastest-growing international companies in its sector. We are headquartered in London and have more than 1700 staff with a presence in more than 25 countries worldwide. Cultural diversity is part of what makes Ebury a special place to be.
What We Offer
We offer a variety of meaningful and competitive benefits to meet your needs, including a competitive salary, continuous professional growth, equity process, and continued personal development through training and certification.
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- Work on reducing technical debt by addressing code that is outdated, inefficient, or no longer aligned with best practices or business needs.
- Help to implement data governance policies, including data quality standards, data access control, and data classification.
- 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 data 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.
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