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Software Engineer

Netflix - 1d ago

Company Logo
Senior Software Engineer

Reddit - 4d ago

Staff Software Engineer

Requirements

  • Commercial development skills in OO programming (C#, Java or C++) and design
  • Cloud-based platform experience (AWS, Azure or Aliyun)
  • Excellent understanding of Agile development methodology and development practices
  • Experience in Agile Scrum tools (such as Jira)
  • Understanding of designing web-based, service-oriented applications and integrated back-office systems
  • Experience in distributed source control system (such as Git)

What you'll be doing

  • You will participate actively in all aspects of designing, building, and delivering products for our clients.
  • Develop with a variety of platforms and technologies, such Docker, Kubernetes, Gitlab, AWS, Azure, Aliyun, .NET Core, Java, Scala, SQL Server, GraphQL.
  • Participate in design reviews and proof of concepts.
  • Contribute to solution design in line with our overall technical roadmap and industry best practices.
  • We have dozens of individual, mission-focused teams working across a wide spectrum of technological challenges. You will have the opportunity, depending on your interests and aptitude, to work on large-scale distributed systems coordinating thousands of servers in cloud and physical data centers around the world, petabyte-scale data challenges, machine learning, advanced visualizations, and interactive user interfaces – to name a few.
  • Staff Engineers contribute to more than our product – they build up our team. Through a combination of mentoring, technical leadership, and/or direct management of small teams, they make others better and raise the bar for those around them.
AI Summary ✨
The Trade Desk logo

The Trade Desk

Madrid, Spain

Experience: Staff
Posted: June 8, 2026
Last seen: 32 minutes ago
Aws
Azure
Docker
Git
Graphql
Java
Kubernetes
backend

Why we track The Trade Desk

The Trade Desk has EU offices and works on programmatic advertising infrastructure. It's not the most glamorous space, but the engineering challenges around real-time bidding, data processing at scale, and ML are technically deep.

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