Staff Software Engineer - Data

JobCubby; Lavamünd; Hybrid; EUR 191.000 - 255.000; Vollzeit

Benefits dieser Stelle

Competitive salary

Fully remote-first

Equity program

Paid time off

Parental leave

Travel opportunities

Home-office setup

Zusammenfassung

JobCubby, on behalf of a partner company, seeks a Staff Software Engineer - Data for a Switzerland-based role. You will shape how blockchain data is ingested, modeled, processed, stored, and delivered to users and developers.

This remote-first, async-friendly position blends deep CS foundations with distributed systems, data engineering, architecture, and practical product thinking. You will work across Go, Kotlin, Rust, and Python to solve high-impact problems with ownership and impact.

Qualifikationen

• Strong CS fundamentals and distributed data systems experience.
• Experience designing and shipping large-scale data platforms.
• Ability to translate requirements into technical designs and plans.
• Proven track record mentoring engineers.
• Experience with Go, Kotlin, Rust, and Python.

Aufgaben

• Translate product requirements into robust design and interfaces.
• Break work into executable pieces with clear ownership.
• Own critical data platform components end-to-end.
• Design for large-scale ingestion, processing, and storage.
• Mentor engineers and contribute to engineering standards.
• Collaborate with product teams and customers to clarify needs.
• Apply AI-assisted tooling with quality control.

Kenntnisse

Distributed systems

Go

Kotlin

Python

Tools

Go

Kotlin

Rust

Python

Jobbeschreibung

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Software Engineer - Data based in Switzerland.

This is a high-impact engineering role focused on the foundations of a large-scale, multi-chain data platform.

You will shape how blockchain data is ingested, modeled, processed, stored, and delivered to users and developers.

The role combines deep computer science, distributed systems, data engineering, architecture, and practical product thinking.

You will take ambiguous requirements and turn them into clear technical designs, delivery plans, and production-ready systems.

Working across Go, Kotlin, Rust, and Python, you will solve challenging problems where correctness, scale, and performance matter.

You will influence architectural direction, raise engineering standards, and help other engineers grow within a highly distributed team.

The environment is remote-first, collaborative, async-friendly, and designed for engineers who enjoy ownership and solving complex problems from first principles.

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.