Staff Software Engineer - Data Integration Services
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Requirements
• A passion for the craft — a drive for engineering excellence and a commitment to raising technical standards across teams. • A passion for the craft • Strong software engineering foundations — algorithms, data structures, and system design, with a focus on building clean, maintainable, and testable systems. Strong command of Golang and Python. • Strong software engineering foundations • Golang and Python • Distributed systems experience — proven track record designing and operating production systems where data movement, consistency, and scalability are core concerns. • API and platform design maturity — experience designing systems composed of multiple services or subsystems, with attention to long-term evolution, schema governance, and sustainable integration patterns. • API and platform design maturity • Architectural breadth — experience designing secure multi-tenant systems and navigating tradeoffs across storage models, compute environments, and cloud infrastructure. • Architectural breadth • Reliability and observability mindset — experience defining operational guarantees, monitoring complex systems, and diagnosing production issues in distributed environments. • Reliability and observability mindset • Security and governance awareness — experience designing access control and data isolation mechanisms, ideally including fine-grained or relationship-based authorisation models. • Security and governance awareness • Cloud-native data systems experience — familiarity with object storage ecosystems and an understanding of filesystem and POSIX semantics, including the tradeoffs when adapting file-based workflows to distributed architectures. • Diagnostic and optimisation skills — ability to identify performance bottlenecks across I/O, storage, and large-scale data workflows. • Proven technical leadership — experience setting technical direction, driving consensus across teams, and delivering platform capabilities adopted beyond a single service. • Proven technical leadership • Communication and influence — ability to translate complex architectural ideas into actionable direction for engineers, product stakeholders, and leadership; experience mentoring and guiding engineers across the organisation. • Communication and influence • Ideally • Ideally • Experience building developer-facing data platforms or internal data infrastructure. • Exposure to ML, simulation, or HPC workflows with large-scale datasets. • Familiarity with data virtualisation or access acceleration technologies. • Experience enabling hybrid or externally hosted compute to securely access shared data. • Knowledge of dataset cataloging, metadata systems, or lineage tracking. • Experience designing scalable alternatives to filesystem-based integration patterns. • Prior experience shaping platform capabilities adopted organisation-wide.
Responsibilities
• Define and drive the technical vision for Data Integration Services as a shared platform capability. • Design scalable, cloud-native data access patterns supporting simulation, ML, and platform workloads without tightly coupled mounting solutions. • Establish consistent abstractions for accessing datasets across APIs, services, and compute environments. • Object storage platforms (S3-compatible systems, Azure Blob, GCS, MinIO) • Managed storage and filesystem abstraction platforms (e.g. FSx, JuiceFS, Alluxio, or similar systems) • Protocol-based access layers such as WebDAV or HTTP-based data interfaces • Translate filesystem-oriented workflows into reliable distributed service patterns where appropriate. • Enable efficient data sharing across teams and tenants while maintaining strong isolation and governance controls. • Design dataset lifecycle capabilities including provisioning, versioning, and retention strategies. • Define how permissioning integrates into the data plane and is enforced consistently across services and workflows. • Partner with platform identity and security teams to ensure consistent access enforcement. • Define standards for data contracts and compatibility between services. • Evaluate build-vs-buy decisions across storage, data access, and metadata tooling. • Establish observability and performance practices for large-scale data workflows. • Mentor engineers and drive cross-team adoption of shared data integration patterns.
Benefits
• Equity options – share in our success and growth. • 10% employer pension contribution – invest in your future. • Free office lunches – great food to fuel your workdays. • Flexible working – balance your work and life in a way that works for you. • Hybrid setup – enjoy our new Shoreditch office while keeping remote flexibility. • Enhanced parental leave – support for life’s biggest milestones. • Private healthcare – comprehensive coverage. • Personal development – access learning and training to help you grow. • Work from anywhere – extend your remote setup to enjoy the sun or reconnect with loved ones. • We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics. • We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.