Backend Engineer

BreezoMeter is looking for a Backend Engineer with the creativity, professionalism and passion to develop innovative data driven backend systems that impact the lives of millions of users around the world. In this position you’ll be working with exceptional people in a multidisciplinary R&D team to create inspiring data driven solutions that you can be proud of

We Are Looking For People Who Are

  • Curious and enthusiastic to learn new things
  • Independent in their approach and learning
  • Team players
  • Thoughtful, positive and proactive
  • Flexible and possess a “can-do” attitude
  • Love everything about cloud technologies
  • Passionate about data related technologies and not afraid of learning and using data analytics tools


  • Take ownership of the design, coding and maintenance of parts of a large-scale data processing system
  • Be involved in designing real-time data processing pipelines and assist in building and integrating cutting edge environmental ML models
  • Collaborate with R&D, algorithm, data science and product teams to solve complex technical and product problems
  • Take a leading part in defining the technical and infrastructural roadmap for all backend components of the system


  • Minimum of 4-5 years of full-time experience in Backend and/or Data Engineering positions
  • Experience in designing and building software that’s extensible, reusable and above all simple to maintain
  • Experience and deep familiarity with at least one of Python or Java
  • Familiarity with big data management concepts and architectures
  • Experience building large-scale, distributed data processing pipelines and systems
  • Familiarity with one of the leading public cloud platforms (preferably Google Cloud Platform), and specifically with serverless development
  • Familiarity with Dockerized applications and experience maintaining them in production

Bonus Points

  • Bachelor's degree in CS or related field
  • Familiarity with common container orchestration & monitoring frameworks and tools (e.g. k8s, Prometheus)
  • Familiarity with common Data Science and Analysis tools and frameworks (e.g. NumPy, Pandas, Scikit-Learn)
  • Familiarity with ML concepts and tools
  • Experience in building complex ETL pipelines