Data Engineer


Information Technology
level required
Mid-Senior Level
job timing

Job Description


To build a data platform to help our researchers and data scientists to quickly and accurately answer to the world’s hardest questions depend on quantitative research. 🙂

If you have experience in shipping scalable software solutions working with large data and throughput volumes and you can quickly learn new and emerging technologies – scroll down and learn more!

As a Data Engineer you will contribute to the full development lifecycle from data to pipelines to DevOps and to support our colleagues in Data Science and Research teams.

What will you do

  • Work closely with our CTO, Software and Data engineers, researchers and data scientists on
    • setting up our technology stack
    • establishing the architecture of our robust data processing pipeline and extensible machine learning platform
    • building robust data pipelines of high data quality in a scalable fashion (both data and maintainability)
    • creating ETL data flows in Big Data Ecosystem


What will you need

  • 5+ years of data engineer or software engineering experience
  • Graduate degree (Ph.D preferred) in a quantitative or analytical field with material exposure to coding
  • Fluent English


  • Good communication skills
  • Detail-oriented, ability to multitask and work in a fast-paced environment
  • Ability to work independently while also being a strong team player


  • Flask and Machine Learning and AI experience


Must haves:

  • Python/R (modelling)
  • Python/Go/Java (platform and runtime)


  • AWS ecosystem (Fargate, S3, SQS, SNS, Lambda, RDS)
  • Docker (containers)
  • Zookeeper (management)
  • Spark/Apache Drill/Athena and similar
  • NGINX (load balancer)
  • Ansible ( application deployment)
  • Jfrog Artifactory (Repository Manager)
  • CircleCI (Continuous Integration)
  • Log and APM tools
  • MongoDB and Redis (NoSQL)
  • PostgreSQL

Additional Information

What can we offer:

  • The chance to solve the most pressing challenges on a global scale
  • Professional development: books, online training
  • Opportunity to attend or speak on conferences
  • Opportunity for travel
  • Flexible working hours
  • Home office opportunity
  • Healthcare benefit package
  • Eye-glasses allowance
  • Excellent salary and compensation package
  • You can choose your working tools (Mac or Windows)
  • Relocation allowance

Place of work: Budapest