About the role
Axiom’s mission is to empower developers to get the best insights into their data, as fast as possible. We are a remote-first and globally distributed team building a cloud native, serverless data analytics platform. Axiom completely changes the way in which developers and organizations think about their data: they can now send unlimited data with cost-effective storage and lightning-fast querying.
As a software engineer on the EventDB team, you will join a collaborative team of Go engineers. You will help maintain and improve the custom high-performance time-series database that Axiom has built from the ground up. You will be working on the cutting-edge of database design in a global fully-remote environment.
What You Will do:
Design and implement various components of our event database product, from ingestion to storage to querying
Write high-quality Go code
Collaborate in design discussions and provide thoughtful code review
Maintain and improve the eventDB codebase health and system performance
Work with cross-functional teams to roll out joint features
Troubleshoot and resolve issues in production environments
Coordinate and monitor production deployments
Work on our custom compiler for APL, the Axiom Processing Language
Occasionally work with customers to discover new requirements or provide support
Must-Have Qualifications
Creative problem-solver with a positive can-do attitude
2+ years experience with the Go programming language
Excellent communication skills, strong collaborative mindset and team-oriented approach
Proven ability to work independently and take ownership of projects
Experience with code review processes and collaborative development
Experience with distributed systems and low-level high-performance applications
Bonus Qualifications
Located in the European Union OR availability to overlap at least 4 hours with EU working hours (9:00-17:00 CET)
Experience building and maintaining compilers/database systems
Basic knowledge of Postgres, Kubernetes and common AWS services
Knowledge of performance optimization techniques
Familiarity with low-level protocol design
Foundations in statistics and math
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