AWS Cloud Engineer | S3 | Data & AI Domain | Milton Keynes

Job description

AWS Cloud Engineer | S3 | Data & AI Domain | Milton Keynes Country: United Kingdom IT STARTS HERE Santander (www.santander.com) is evolving from a global, high-impact brand into a technology-driven organisation, and our people are at the heart of this journey. Together, we are driving a customer-centric transformation that values bold thinking, innovation, and the courage to challenge what’s possible. This is more than a strategic shift. It’s a chance for driven professionals to grow, learn, and make a real difference. Our mission is to contribute to help more people and businesses prosper. We embrace a strong risk culture and all our professionals at all levels are expected to take a proactive and responsible approach toward risk management. The Data & AI Domain at Santander is responsible for setting the strategic direction for data, analytics, and artificial intelligence across the organisation. It ensures that data is managed as a trusted enterprise asset and that advanced technologies are applied responsibly, securely, and effectively to create value for customers and the business. THE DIFFERENCE YOU MAKE The Data & AI Domain is looking for a AWS Cloud Engineer based out of Milton Keynes. In this role, you will be responsible for engineering, operating, and evolving the AWS data lake platform, including the cloud infrastructure, shared services, and data engineering applications that sit on top of it. You will work closely with data engineering, analytics, security, and architecture teams to ensure the platform is secure, resilient, cost‑effective, and scalable, enabling teams to deliver data products safely and efficiently. This is a hands‑on engineering role, focused on building and running cloud platforms rather than line management. The difference you’ll make: Support the engineering, operation, reliability and continuous improvement of Santander's AWS data lake. Build, configure and support AWS platform capabilities using services such as S3, IAM, VPC, KMS, CloudWatch, CloudTrail, Glue, Athena, EMR, Lambda and Step Functions, following approved designs and standards. Develop and maintain Infrastructure as Code for AWS environments and reusable platform components, with guidance from experienced engineers. Contribute to CI/CD pipelines and deployment automation that support safe, repeatable and controlled platform changes. Apply approved cloud security controls, including least-privilege access, encryption, network isolation, secrets management and policy enforcement. Provide operational support for Spark, batch and, where required, streaming workloads running on the platform. Support platform resilience through monitoring, alerting, incident response, problem investigation and maintenance of operational runbooks. Identify opportunities to improve performance, capacity and cloud cost, escalating recommendations through the appropriate engineering channels. Work with Data Engineering, Analytics, Security, Architecture and Risk teams to deliver platform changes in line with Santander standards and regulatory expectations. We’re shaping the way we work through innovation, cutting-edge technology, collaboration and the freedom to explore new ideas. To succeed in this role, you will be responsible for: Deliver assigned AWS data lake platform changes and operational activities to agreed quality, control and timescale expectations. Follow regulatory requirements, the Santander Operational Risk Framework and internal technology standards, raising risks or control gaps promptly. Configure and support secure multi-account AWS environments in line with approved architecture and engineering patterns. Develop and maintain Infrastructure as Code modules and reusable components, contributing to consistent delivery across teams. Use CI/CD and release controls to promote infrastructure and platform changes safely across development, test and production. Monitor platform health, performance and cost, using observability tooling to identify issues, investigate causes and support improvement actions. Help identify and remediate technology obsolescence, platform risks, resilience gaps and operational control weaknesses, escalating complex issues when required. Work with Enterprise Architecture, Data Architecture, Security, Risk and Data Engineering to deliver changes aligned with approved architectures and standards. WHAT YOU’LL BRING Our people are our greatest strength. Every individual contributes unique perspectives that make us stronger as a team and as an organisation. We’re enabling teams to go beyond by valuing who they are and empowering what they bring. The following requirements represent the knowledge, skills, and abilities essential for success in this role. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Professional Experience AWS Platform Engineering: Proven experience engineering, operating, and evolving secure, resilient, and scalable AWS platforms supporting enterprise data and analytics workloads. (Required) Infrastructure as Code and Automation: Experience delivering cloud infrastructure through Infrastructure as Code and automation practices, enabling consistent, repeatable, and controlled management of AWS environments and platform services. (Required) DevOps and CI/CD: Experience applying DevOps and CI/CD practices to manage the build, release, deployment, and controlled promotion of cloud platform changes across enterprise environments. (Required) Data Lake and Analytics: Experience supporting enterprise data lake and analytics platforms, including the infrastructure and platform capabilities required for batch, streaming, and near-real-time workloads. (Required) Security, Operations and FinOps: Experience operating AWS platforms with responsibility for cloud security, observability, operational resilience, capacity management, and cost optimisation within an enterprise environment. (Required) Agentic AI and AI-Assisted Engineering: Experience or practical exposure to agentic AI and AI-assisted engineering tools and technologies. (Required) Way of working: Experience working with agile or product-aligned delivery models, and emerging technologies such as Agentic AI within data engineering environments. (Preferred) Education Degree in software engineering, computer science or related field (Required) Desirable AWS certification (e.g. AWS Solutions Architect – Associate, AWS CloudOps Engineer or AWS Data Engineer) (Preferred) Languages English Spanish (Preferred) Hard Skills AWS Platform Engineering Hands-on experience with AWS cloud architecture, including key services like S3, IAM, VPC, KMS, CloudWatch, CloudTrail, Glue, Athena, EMR, Lambda, Step Functions, and SageMaker. (Required) Build and operate secure, resilient, and scalable multi-account AWS environments for enterprise data lake and analytics workloads. (Required) Strong experience managing AWS data and analytics platforms, including application and framework management, supporting batch and streaming workloads from a platform and infrastructure perspective. (Required) IaC and CI/CD Hands-on experience with Infrastructure as Code (IaC), using tools such as Terraform, CloudFormation, or AWS CDK to provision and manage secure, consistent, and repeatable AWS environments and platform services. (Required) Strong experience with CI/CD practices and tooling, such as Git, Jenkins, GitHub Actions, or AWS CodePipeline, to automate build, testing, deployment, and controlled promotion of platform changes across environments. (Required) Data Lake and Analytics Experience in data ingestion, processing, transformation, and delivery using batch, streaming, and real-time methods. (Required) Skilled in SQL and NoSQL databases for implementing data warehouses and data lakes. (Required) Data lake platform operations, including ingestion frameworks, access layers, shared services and workload support