Data Platform Engineer for Global Expansion

hace 4 semanas


Madrid, Madrid, España Ebury A tiempo completo

About Our Company

Ebury is a hyper-growth FinTech firm recognized as one of the top 15 European Fintechs to work for by AltFi. With a strong presence across 27 offices worldwide, we serve over 45 clients every day.

Job Description

We are seeking a Senior Data Engineer to join our Data Engineering team. As a key member of our data mission, you will develop and maintain Ebury's Data Platform, serving it to the whole company.

Key Responsibilities:

  • Build and maintain 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.

Required Skills and Qualifications

To succeed in this role, you will need:

  • At least 4+ 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.
  • A plus: Experience with modern Data stack tools, dimensional modelling/data warehousing concepts knowledge, Spanish language.

About the Role

As a Senior Data Engineer, you will work closely with the rest of the team to help model and maintain the Data Platform.

What We Offer

In this role, you will have the opportunity to:

  • Be mentored by one of our outstanding performance team members 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.
  • Serve hands-on delivery of data models using solid software engineering practices.
  • Manage overall pipeline orchestration using Airflow.
  • Work on reducing technical debt by addressing code that is outdated, inefficient, or no longer aligned with best practices or business needs.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.
  • Help to implement data governance policies.
  • Identify opportunities to optimize and refine existing processes.

Salary

$120,000 - $180,000 per year, depending on experience.



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