Senior Software Enginner

Lead Backend Software Engineer – Data ServicesFederated Data Services | Distributed Systems | Apache Spark | DataFusion | Python | KubernetesLocation: London (2 days per week onsite)Rate: £700–£800 per day (Outside IR35)Duration: Initial 6-month contract with likely extensionOverviewWe're looking for an experienced Lead Backend Software Engineer to join a high-profile programme building secure, cloud-native data services that will support data-driven research and innovation at national scale.This is a founding engineering role, offering the opportunity to shape the architecture, engineering standards, and core data services from the ground up. Working closely with the Engineering Manager and a small team of senior engineers, you'll establish the technical foundations for a complex federated data platform operating within a highly regulated environment.We're looking for someone who enjoys building from first principles, thrives in ambiguity, and can balance strategic architectural thinking with hands-on software engineering. This role is centred around designing and building distributed data services rather than traditional application development.Role & Responsibilities\n

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• Lead the design and development of scalable, cloud-native data services supporting a federated platform.
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• Define architectural patterns, engineering standards, and best practices that will scale across the wider organisation.
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• Design and build distributed server-side services using modern software engineering practices.
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• Architect and develop federated data services capable of securely querying and processing data across multiple environments.
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• Design high-performance data processing and streaming workflows using technologies such as Apache Spark, Apache DataFusion, or similar distributed query frameworks.
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• Design and implement Kubernetes-based services and containerised workloads.
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• Build secure APIs and backend services supporting authentication, authorisation, governance, and audit requirements.
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• Contribute to the design of distributed systems, data pipelines, and platform architecture.
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• Establish CI/CD pipelines, Infrastructure as Code, automated testing, and deployment practices.
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• Evaluate and integrate open-source technologies and distributed data frameworks.
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• Mentor engineers and promote engineering excellence across the team.
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• Work closely with architecture, product, security, and external stakeholders.
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Skills & ExperienceEssential\n

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• Experience as a Lead Engineer, Principal Engineer, Staff Engineer, Software Architect, or similar senior technical role.
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• Strong server-side software engineering experience, with flexibility across programming languages such as Python, Java, Go, Scala, C#, or similar.
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• Experience designing and building distributed data services or large-scale backend platforms.
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• Experience with Apache Spark, Apache DataFusion, Trino, Presto, or similar distributed data processing technologies.
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• Strong architecture and design experience across distributed systems and data services.
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• Experience designing scalable data processing or data streaming workflows.
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• Experience building cloud-native applications on AWS, Azure, or GCP.
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• Experience with Kubernetes, Docker, and containerised environments.
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• Experience building and operating CI/CD pipelines and Infrastructure as Code.
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• Strong understanding of distributed systems, scalability, resilience, and secure-by-design principles.
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• Comfortable making architectural decisions within evolving, fast-paced environments.
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• Excellent communication skills with the ability to work across technical and non-technical teams.
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Desirable\n

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• Experience building federated data services or federated data platforms.
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• Experience within healthcare, life sciences, research, government, or other highly regulated environments.
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• Knowledge of Trusted Research Environments (TREs), Secure Data Environments (SDEs), or similar secure data platforms.
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• Experience with data governance, metadata services, data catalogues, or secure data access models.
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• Exposure to event-driven architectures and streaming technologies such as Kafka, Flink, or Spark Streaming.
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• Experience evaluating or contributing to open-source technologies.
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