Staff Data Platform Engineer - Remote, Equity, PTO

Dune

Les Ulis

On-site

EUR 90,000 - 140,000

Full time

14 days+

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Benefits offered by this job

Salary & equity
Remote-first
5 weeks PTO
Private medical insurance
Parental leave
Offsites

Job summary

Dune is seeking an engineer for Data Foundation to own how blockchain data enters Dune, how it is represented and delivered externally. You will design scalable distributed data systems, define interfaces, and deliver core data workflows.

You’ll hand ambiguous product requirements to a design and plan, while executing with the team to build the hardest parts yourself. You will collaborate across Go, Kotlin, Rust, and Python, focusing on correctness, performance, and scalable data processing in a

Responsibilities

  • Turn product requirements into technical requirements: model the domain, define the interfaces and the workflows, and navigate trade-offs
  • Break large problems into work other engineers can own, and sequence it so we ship something useful early
  • Drive high-impact architectural decisions across the data platform, and own components end to end from design through production
  • Work across our stack, mainly Go, Kotlin, Rust and Python where they fit, choosing the right tool rather than the familiar one
  • Design for correctness and performance under real volume: large-scale ingestion, distributed processing, and data lake storage
  • Raise the bar on design reviews, testing, and how the team breaks work down
  • Mentor engineers by example, in a fully distributed team

Job description

Dune is seeking an engineer for Data Foundation to own how blockchain data enters Dune, how it is represented and delivered externally. You will design scalable distributed data systems, define interfaces, and deliver core data workflows.

You’ll hand ambiguous product requirements to a design and plan, while executing with the team to build the hardest parts yourself. You will collaborate across Go, Kotlin, Rust, and Python, focusing on correctness, performance, and scalable data processing in a

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