Staff Software Engineer - Data

Accountabilities

• Translate product requirements into robust technical solutions by modeling domains, defining interfaces and workflows, identifying constraints and invariants, and making thoughtful architectural trade-offs.
• Break complex initiatives into well-defined pieces of work that can be owned by multiple engineers, sequencing delivery so useful functionality reaches production early.
• Drive high-impact architectural decisions across the data platform and take end-to-end ownership of critical components from initial design through production operation.
• Design and build systems capable of handling real-world scale, including large-scale data ingestion, distributed processing, and data lake storage while maintaining strong standards for correctness and performance.
• Work across the engineering stack, primarily using Go, Kotlin, Rust, and Python, selecting technologies based on the problem rather than relying on familiar tools.
• Apply strong computer science fundamentals to distributed data systems, explicitly considering contracts, state transitions, invariants, failure modes, fault models, and scaling limitations.
• Raise engineering standards through strong design reviews, effective testing practices, thoughtful decomposition of technical work, and clear engineering processes.
• Collaborate closely with product teams, customers, and engineers to clarify ambiguous requirements, define appropriate scope, and confidently guide technical decisions.
• Mentor engineers through hands-on leadership and example, helping strengthen technical judgment, system design, and execution practices across a fully distributed team.
• Use AI-assisted engineering tools thoughtfully to improve productivity while maintaining high standards for code quality, reasoning, correctness, and maintainability.
• Contribute to continuous improvement of the data foundation, identifying opportunities to improve scalability, reliability, developer experience, and the quality of the platform’s underlying architecture.

Requirements

• Strong software engineering background with solid computer science fundamentals and the ability to adapt quickly to unfamiliar technologies, systems, and problem spaces.
• Demonstrated experience designing and shipping distributed data systems, with a practical understanding of their architecture, contracts, state management, invariants, failure modes, fault tolerance, and scaling characteristics.
• Strong first-principles problem-solving approach, with the ability to make assumptions explicit, identify meaningful constraints, and derive solutions rather than simply applying familiar patterns.
• Experience working on large-scale systems where correctness, performance, reliability, and operational behavior are critical considerations.
• Ability to work effectively with ambiguity by engaging product, customers, and engineering stakeholders, defining a clear scope, and taking ownership of the resulting technical direction.
• Strong ability to translate complex product requirements into technical requirements, architectural designs, implementation plans, and actionable engineering tasks.
• Experience working across multiple programming languages and technologies, with the flexibility to select the most appropriate tool for a given problem.
• Strong written and verbal communication skills, particularly in distributed and asynchronous environments where clear documentation and thoughtful written communication are essential.
• Demonstrated ability to influence engineering standards, conduct effective design reviews, improve development practices, and mentor other engineers.
• Strong practical experience with AI-assisted development tools, including an understanding of their capabilities, limitations, and failure modes, combined with a high bar for avoiding low-quality or unreliable AI-generated output.
• Ability to operate independently, prioritize effectively, and maintain ownership in a remote-first environment with a high degree of autonomy.
• Experience with data lakes and modern storage formats such as Parquet, Apache Iceberg, or Delta Lake is a plus.
• Experience working at a company or product organization where data itself is a core part of the product is a plus.

Benefits

• Competitive salary and equity package positioned within the top 25% of comparable companies in the space.
• Employee equity program with employee-friendly terms, including an approximately 90% discounted strike price and a 10-year exercise window.
• 5 weeks of paid time off plus local public holidays, with flexibility to swap holidays where appropriate.
• Fully remote-first working model within a distributed international team.
• Flexible working hours, giving you significant autonomy to structure your working day.
• Strong async-first culture designed to reduce unnecessary meetings and protect focused deep-work time.
• Private medical insurance, including dental and vision coverage.
• Fully paid parental leave of 16 weeks for primary caregivers and 6 weeks for secondary caregivers, plus a 2-week part-time phased return at full pay.
• Quarterly company or team offsites in different international locations to connect, collaborate, and spend time together.
• Annual travel allowance to enable employees to connect and co-work with colleagues for several days.
• Home-office setup allowance, with local coworking space costs covered if preferred.
• Opportunity to work alongside highly experienced engineers and colleagues in a collaborative, distributed environment.
• Opportunity to work on challenging data infrastructure and blockchain analytics problems with significant technical ownership and impact.
• Company merchandise and other team perks.