Job Summary
JOB DESCRIPTION Senior Platform Engineer – Data & Cloud Platforms Role Overview Job Title Senior Platform Engineer Function Data & Cloud Platform Engineering Location London, United Kingdom Seniority Senior Engineer Reporting Line Reports to Platform Lead / Delivery Lead Purpose of the Role The Platform Engineering team is responsible for the end-to-end reliability, automation, and continuous improvement of a large-scale enterprise data platform. Operating as the technical authority within a lean platform team, the role drives the design, delivery, and operational excellence of data infrastructure spanning workflow orchestration, lakehouse and analytics platforms, cloud services, and container orchestration. The incumbent provides technical leadership across incident response, platform architecture decisions, CI/CD strategy, and stakeholder engagement — ensuring the platform consistently meets the evolving demands of a large engineering community. Key Responsibilities Platform Engineering & Architecture Design, deploy, and operate workflow orchestration platforms in containerised environments, ensuring high availability across multiple deployment environments. Lead administration of lakehouse and analytics platforms, including environment lifecycle management, access governance, and data sharing with internal and external consumers. Manage cloud infrastructure including compute, managed databases, object storage, and identity & access management; own upgrade planning and change documentation. Drive container platform engineering including workload scheduling, namespace resource governance, and operator lifecycle management. Observability & Reliability Build and maintain end-to-end observability solutions including metrics dashboards, alerting pipelines, and centralised log aggregation across distributed platform components. Lead investigation and resolution of platform-level incidents; conduct root cause analysis and implement lasting fixes across networking, storage, and scheduling layers. Define and own service level objectives for platform services; proactively drive reliability improvements through automation and systematic monitoring. CI/CD & Automation Own end-to-end CI/CD pipelines including automated testing, scheduled build strategies, and dependency management across multiple pipeline toolchains. Design and maintain autoscaled containerised build agent infrastructure; implement graceful lifecycle patterns and declarative deployment tooling. Champion infrastructure-as-code and configuration management practices; manage templated deployments and version-controlled platform component definitions. Stakeholder Engagement & Leadership Serve as the technical point of contact for engineering teams, product owners, and senior stakeholders; communicate complex platform decisions clearly across technical and non-technical audiences. Lead change management processes including change records, impact assessments, and post-implementation reviews in regulated enterprise environments. Provide on-call coverage and coordinate incident escalation; contribute to team knowledge sharing and cross-functional capability development. Produce platform capability documentation, capacity assessments, and technical reporting for leadership and governance audiences. Skills & Experience DevOps, cloud infrastructure (AWS/Azure), DevOps automation, observability, CI/CD, and enterprise tooling and enterprise tooling. Strong expertise in AWS, Azure, Kubernetes/OpenShift, Apache Airflow, Databricks, Unity Catalog, Splunk, Azure DevOps, Jenkins, and ALM platforms. Proven experience operating workflow orchestration platforms in Kubernetes or container-based environments. Hands-on experience administering lakehouse or data warehouse platforms including access control, lineage, and multi-environment management. Solid cloud platform engineering experience across compute, storage, managed datab
Key Responsibilities
Skills & Experience
- DevOps, cloud infrastructure (AWS/Azure), DevOps automation, observability, CI/CD, and enterprise tooling and enterprise tooling. Strong expertise in AWS, Azure, Kubernetes/OpenShift, Apache Airflow, Databricks, Unity Catalog, Splunk, Azure DevOps, Jenkins, and ALM platforms.
- Proven experience operating workflow orchestration platforms in Kubernetes or container-based environments.
- Hands-on experience administering lakehouse or data warehouse platforms including access control, lineage, and multi-environment management.
- Solid cloud platform engineering experience across compute, storage, managed databases, and identity management.
- Expertise in Kubernetes or equivalent container orchestration including resource management and declarative deployment tooling.
- Strong CI/CD pipeline design and ownership experience across at least one major pipeline platform.
- Practical observability engineering: metrics collection, dashboarding, alerting, and log management.
- Proficiency in scripting and automation (Python and/or Bash) for platform tooling and operational tasks.
- Demonstrated experience leading incident management and participating in on-call rotations.
- Experience with autoscaling workload patterns in containerised environments.
- Familiarity with AI/ML platform infrastructure or managed AI service observability.
Leadership Behaviours
- Takes ownership: Proactively identifies platform risks and drives resolution without needing direction.
- Raises the bar: Continuously introduces automation and best practices to improve platform reliability and team capability.
- Communicates with clarity: Translates technical complexity into actionable insight for both engineering and business audiences.
- Collaborative: Works effectively across vendor, partner, and client teams in a matrix organisation.
- Adaptable: Comfortable operating with ambiguity in fast-moving, multi-cloud enterprise environments.
About the Team
The Platform Engineering team is a specialist unit responsible for the foundational data infrastructure that enables engineers, analysts, and scientists to operate at enterprise scale. The team covers workflow orchestration, lakehouse platforms, cloud infrastructure, and the observability and CI/CD tooling that underpins the entire data platform. The team operates with a high degree of autonomy and ownership, spanning platform engineering, incident response, and strategic architecture decisions.