Staff Software Engineer - Data

Job description

About Dune Dune is on a mission to make crypto data accessible. We’re a collaborative multi-chain analytics platform used by thousands of developers, analysts, & investors to understand the on-chain world and the frontiers of finance. We’re a team of ~60 employees, working together across Europe and eastern US timezones ️. We believe in our mission, and in building a powerful, open product that allows individuals and communities to do deep research into important ecosystems like Bitcoin, Ethereum, Solana, and many more. We’re backed by some of the world's best investors. In February 2022, we announced our Series B funding round led by Coatue and Union Square Ventures, an important milestone that allowed us to double down on our mission. We’re using the funds to educate, reward and empower a new generation of onchain analysts aka Wizards ‍♀️ If you want to have one of the highest impact jobs on the planet, come join our wonderful team of Galaxy brains. Learn more about us: Dune's Vision Values and working at Dune About the role Data Foundation owns how blockchain data enters Dune, how it is represented and how it’s delivered externally. This is a role that involves thinking about large distributed data systems, recognising traditional scaling patterns and software lifecycle pitfalls, and is ideal for anyone passionate about those topics. You will be the engineer we hand ambiguous product requirements to, and will be comfortable coming back with a design, a sequence, and a set of tasks the team can pick up as well as building the hardest parts yourself. In this role you will 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 You might be a great fit if You are a s…