Ramat Gan, Israel
Full time

C Developer

Ramat Gan, Israel
Full time

Varada is rapidly growing and looking for an experienced and talented Infrastructure developer to join our small and unique team and help us to take our product to new heights.

We develop one of the most innovative development Big Data systems in the world using the latest technologies.

As a team member you will influence the culture and standards of our rapidly growing R&D organization, involved in the design, implementation and stabilization of Varada core features.

  • Build and improve our infrastructure
  • Contributing in all development phases (from requirements to release)
  • Designing and implementing best practices and new features
  • Supporting internal and external customers
  • Dive into Presto open source
Job Requirements:
  • 5+ years experience in C development
  • Linux as a working environment
  • Ability to deep dive into large scale existing projects
  • Good understanding of best practices in scalable server side architecture
  • Autodidact and self-motivated
  • True team player
  • Experience working in a startup company – advantage
  • Experience with Big Data platforms/DBs – advantage
  • Experience working in open source environment – advantage
  • Familiarity with AWS/GCP – advantage
We look forward to hearing from you!
Email us at job@varada.io


Vara-da comes from an old Hindu word that is used to describe a boon giver, relief for pain. When it comes to data, there are still many types of pain. In some organizations the focus is on data democratization with challenges around exposing data to as many consumers as possible. For other organizations the focus is on enabling data consumers to ask any questions without compromising on time-to-insight and performance.
Varada offers a big data infrastructure solution for fast analytics on thousands of dimensions. Based on Varada’s Inline Indexing™ technology, we enable large and complex datasets to optimally serve analytics users and apps by making filtering, joining and aggregating data extremely fast on every dimension of any data source.
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