Principal Software Engineer - Datapath

We are looking for a Principal Data Path Engineer to help advance the core technology behind our cloud-native file data platform. This role is for a deeply technical C++/Linux engineer who has designed, optimised, and debugged performance-critical systems such as storage platforms, file systems, databases, or distributed infrastructure.
In this role, you will own critical data-path capabilities that directly affect performance, scalability, reliability, and customer experience. You will work on complex systems where concurrency, latency, throughput, caching, protocol behaviour, and failure handling matter. You will collaborate with Engineering, QA, Performance Engineering, and Customer Support to improve core platform behaviour and resolve high-priority technical issues.
This role is a strong fit for someone who wants to remain hands-on while influencing architecture, design quality, and engineering practices across teams. It is not a fit for someone focused primarily on people management, application-layer development, or high-level architecture without deep implementation and debugging ownership.
You will independently lead design and implementation for critical data-path components, make technical tradeoffs, and guide durable solutions for complex performance and reliability challenges. You will balance hands-on development with technical leadership, design reviews, mentoring, and cross-functional collaboration.
Responsibilities:
Own the design, implementation, optimisation, and maintenance of critical data-path components within the platform.
Improve read/write behaviour, concurrency, throughput, latency, scalability, and reliability across performance-sensitive system paths.
Lead technical investigations into complex defects, regressions, and customer-impacting escalations.
Partner with QA and Performance Engineering to define test strategies, reproduce issues, measure improvements, and validate production readiness.
Contribute to architecture reviews, coding standards, debugging practices, and technical direction across engineering.
Use AI-assisted engineering tools thoughtfully for code exploration, test generation, debugging hypotheses, documentation, and analysis while validating correctness, security, and maintainability.
Requirements:
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or related technical field.
10+ years of software engineering experience, including 7+ years in storage systems, databases, distributed systems, or performance-critical infrastructure.
Expert-level C++ and/or C programming on Linux.
Strong experience with multi-threaded programming, concurrency, memory management, and systems debugging.
Proven ownership of performance analysis and optimisation using profiling, tracing, or diagnostic tools.
Solid networking fundamentals and experience with application-level protocols.
Clear written and verbal communication skills.
Preferred:
Experience with file systems, NAS, object storage, distributed storage, caching, metadata services, replication, snapshots, or consistency models.
Python or Go experience for tooling, automation, test frameworks, or service integration.
Experience supporting customer escalations or production-impacting engineering investigations.
Familiarity with cloud infrastructure, SaaS product engineering, and secure engineering practices.
Practical use of AI-assisted development workflows with strong validation discipline.
Ideal:
Principal or staff-level ownership of performance-critical data-path architecture in a commercial storage, database, or distributed systems product.
Track record of measurable improvements in throughput, latency, reliability, or incident reduction.
Ability to influence engineers across teams without relying on reporting authority.

Experience
9-13 yrs