Senior AWS Data Engineer

Editx

Mechelen

Sur place

EUR 60 000 - 90 000

Plein temps

14 jours+
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Résumé du poste

Editx in Belgium is seeking an AWS Data Engineer to build, monitor, and maintain reliable data solutions on AWS. You will work with Data Scientists, Analytics Engineers, and Business Consultants to deliver client value.

The role focuses on translating business needs into scalable data pipelines, balancing cost and performance, implementing deployment automation and monitoring, and sharing knowledge with the team. You will mentor junior staff and contribute to architectural decisions.

Qualifications

  • Build and maintain data infrastructure (ELT, pipelines, interfaces between data products)
  • Translate business needs into well-designed, maintainable data solutions
  • Balance cost, performance, and maintainability when designing new or improving on existing solutions
  • Implement production-ready solutions (deployment automation, monitoring, alerting)
  • Stay up to date with developments in data technology and share knowledge with colleagues
  • Coach junior and medior data engineers

Responsabilités

  • Build and maintain data infrastructure (ELT, generic data pipelines, interfaces between data products)
  • Translate business needs into well-designed, maintainable data solutions
  • Balance cost, performance, and maintainability when designing new or improving on existing solutions
  • Implement production-ready solutions (deployment automation, monitoring, alerting)
  • Stay up to date with developments in data technology and share your knowledge with your colleagues
  • Coach junior and medior data engineers

Description du poste

We are looking for an AWS Data Engineer with experience in building, monitoring and maintaining reliable and secure data solutions in AWS. You will work closely with Data Scientists, Analytics Engineers, and Business Consultants to deliver value to our clients.

Your responsibilities
  • Build and maintain data infrastructure (e.g. ELT, generic data pipelines, interfaces between data products)
  • Translate business needs into well-designed, maintainable data solutions
  • Balance cost, performance, and maintainability when designing new or improving on existing solutions
  • Implement production-ready solutions (e.g. deployment automation, monitoring, alerting)
  • Stay up to date with developments in data technology and share your knowledge with your colleagues
  • Coach junior and medior data engineers
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