21 of 21 Amazon S3 Jobs in the City of London

and Waterfall delivery models to meet project goals. · Mentor junior engineers and foster a culture of learning and growth. Required Skills & Experience · Strong expertise in AWS services (e.g., EC2, S3, RDS, Lambda) and/or Azure. · Hands-on experience with Infrastructure as Code tools (Terraform, ARM, BICEP). · Proficiency in containerisation and orchestration (Docker, Kubernetes/EKS). · Skilled More ❯

and Waterfall delivery models to meet project goals. · Mentor junior engineers and foster a culture of learning and growth. Required Skills & Experience · Strong expertise in AWS services (e.g., EC2, S3, RDS, Lambda) and/or Azure. · Hands-on experience with Infrastructure as Code tools (Terraform, ARM, BICEP). · Proficiency in containerisation and orchestration (Docker, Kubernetes/EKS). · Skilled More ❯

data engineer with strong hands-on programming skills and software engineering fundamentals, with experience building scalable solutions in cloud environments (AWS preferred) Extensive experience in AWS services, e.g. EC2, S3, RDS, DynamoDB, Redshift, Lambda, API Gateway Solid foundation in software engineering principles, including version control (Git), testing, CI/CD, modular design, and clean code practices. Experience developing reusable More ❯

infrastructure strategy, drive automation, and strengthen CI/CD practices to keep our technology reliable and scalable. Required Technical Skills 5+ years AWS experience (VPC, EC2, ECS, EKS, EFS, S3, Workspaces, Security Groups, CloudWatch/CloudTrail, IAM). Strong containerization expertise (Docker or similar). Scripting and automation with Python or Bash. Modern CI/CD practices and pipeline More ❯

experience in .NET development , including .NET Core and C# . Strong experience in designing and developing Microservice architectures in cloud environments. Proven experience with AWS services including EC2 , Lambda , S3 , RDS , DynamoDB , SNS , SQS , EventBridge, AWS Amplify , and API Gateway . Familiarity with asynchronous messaging and event-based communication patterns (e.g., event queues , publish/subscribe ). Experience with More ❯

experience in .NET development , including .NET Core and C# . Strong experience in designing and developing Microservice architectures in cloud environments. Proven experience with AWS services including EC2 , Lambda , S3 , RDS , DynamoDB , SNS , SQS , EventBridge, AWS Amplify , and API Gateway . Familiarity with asynchronous messaging and event-based communication patterns (e.g., event queues , publish/subscribe ). Experience with More ❯

Tools like GitHub Actions, Jenkins, AWS CDK, CloudFormation, Terraform. Key Responsibilities: Design and implement scalable, secure, and cost-efficient data solutions on AWS, leveraging services such as Glue, Lambda, S3, Redshift, and Step Functions. Lead the development of robust data pipelines and analytics platforms, ensuring high availability, performance, and maintainability. Demonstrate proficiency in software engineering principles, contributing to the More ❯

Tools like GitHub Actions, Jenkins, AWS CDK, CloudFormation, Terraform. Key Responsibilities: Design and implement scalable, secure, and cost-efficient data solutions on AWS, leveraging services such as Glue, Lambda, S3, Redshift, and Step Functions. Lead the development of robust data pipelines and analytics platforms, ensuring high availability, performance, and maintainability. Demonstrate proficiency in software engineering principles, contributing to the More ❯

ll have the autonomy to make technical decisions and help shape how platform engineering is done as the team continues to scale. Tech stack AWS (Core services - EC2, RDS, S3, IAM, etc.) Configuration Management Ansible Monitoring and Observability Grafana, Prometheus Kubernetes (building and managing production clusters) Terraform (IaC provisioning) Python or Java (scripting, automation) GitHub Actions (CI/CD More ❯

You’ll have the autonomy to make technical decisions and help shape how platform engineering is done as the team continues to scale. Tech stack AWS (Core services - EC2, S3, IAM, etc.) Kubernetes (building and managing production clusters) Terraform (for full IaC provisioning) Python (scripting, automation) GitHub Actions/Azure DevOps (CI/CD pipelines) Docker & Helm (for containerised More ❯

ll have the autonomy to make technical decisions and help shape how platform engineering is done as the team continues to scale. Tech stack AWS (Core services - EC2, RDS, S3, IAM, etc.) Monitoring and Observability Grafana, Prometheus Kubernetes (building and managing production clusters) Terraform (IaC provisioning) Python, Bash or Go (scripting, automation) GitHub Actions (CI/CD pipelines) What More ❯

ll have the autonomy to make technical decisions and help shape how platform engineering is done as the team continues to scale. Tech stack AWS (Core services - EC2, RDS, S3, IAM, etc.) Configuration Management Ansible Monitoring and Observability Grafana, Prometheus Kubernetes (building and managing production clusters) Terraform (IaC provisioning) GitHub Actions (CI/CD pipelines) What They’re Looking More ❯

hands-on technical involvement in key deals. Technical Expertise Cloud-Native Architectures: - Deep understanding of AWS, Azure, and GCP services, including compute (EC2, Lambda), networking (VPC, Transit Gateway), storage (S3, Blob), and container orchestration (ECS, Fargate, Kubernetes/EKS/GKE). - Familiarity with IaC tools such as Terraform, CloudFormation, and Helm for scalable deployments. AI/ML Fundamentals More ❯

security and compliance. Build and maintain CI/CD pipelines, monitoring tools, and cost optimisation strategies. Mentor and coach engineers on platform best practices. Tech Stack Highlights AWS (ECS, S3, DynamoDB, Aurora, OpenSearch) Pulumi (TypeScript) for infrastructure as code Kafka (Confluent Cloud) for event-driven architecture GitHub Actions for CI/CD DataDog for observability Containerised microservices architecture What More ❯

security and compliance. Build and maintain CI/CD pipelines, monitoring tools, and cost optimisation strategies. Mentor and coach engineers on platform best practices. Tech Stack Highlights AWS (ECS, S3, DynamoDB, Aurora, OpenSearch) Pulumi (TypeScript) for infrastructure as code Kafka (Confluent Cloud) for event-driven architecture GitHub Actions for CI/CD DataDog for observability Containerised microservices architecture What More ❯

collaborative development workflows. Good written and verbal communication; able to contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to More ❯

solution design experience with a focus on data projects You have experience of establishing data analytics and supporting AI solutions You have a good working experience of AWS (e.g. S3, Kinesis, Glue, Redshift, Lambda and EMR) and/or Azure data services (e.g. ADF, Synapse, Fabric, Azure Functions) You have advanced client and stakeholder management skills What's in More ❯

ML model deployment and production monitoring. • Working knowledge of core data science concepts, such as model evaluation metrics, overfitting, data drift, and feature importance. • Proficiency in AWS services (like S3, RedShift etc) • Experience with Grafana for monitoring and alerting. • Good to have hands-on experience with Domino Data Lab platform. • Solid understanding of CI/CD pipelines, version control More ❯

ML model deployment and production monitoring. • Working knowledge of core data science concepts, such as model evaluation metrics, overfitting, data drift, and feature importance. • Proficiency in AWS services (like S3, RedShift etc) • Experience with Grafana for monitoring and alerting. • Good to have hands-on experience with Domino Data Lab platform. • Solid understanding of CI/CD pipelines, version control More ❯

modernisation journey to Snowflake-based data warehousing solutions within an AWS environment. Design and implement scalable, secure, and cost-efficient data solutions using AWS services such as Glue, Lambda, S3, Redshift, and Step Functions. Develop robust data pipelines and analytics platforms, ensuring high availability, performance, and maintainability. Drive automation and CI/CD practices for data workflows, ensuring reliable … mentoring teams Proven experience as a data engineer with a strong focus on Snowflake and AWS services in large-scale enterprise environments Extensive experience with AWS services (e.g., EC2, S3, RDS, DynamoDB, Redshift, Lambda, API Gateway) Strong SQL skills for complex data queries and transformations Python programming for data processing and analysis is a plus Strong leadership, communication, and More ❯

next-generation data platform, with responsibilities including: Designing and implementing scalable data pipelines using Python and Apache Spark Building and orchestrating workflows using AWS services such as Glue , Lambda , S3 , and EMR Serverless Applying best practices in software engineering: CI/CD , version control , automated testing , and modular design Supporting the development of a lakehouse architecture using Apache Iceberg … understanding of data engineering fundamentals: ETL/ELT, schema evolution, batch processing Experience or strong interest in Apache Spark for distributed data processing Familiarity with AWS data tools (e.g., S3, Glue, Lambda, EMR) Strong communication skills and a collaborative mindset Comfortable working in Agile environments and engaging with stakeholders Bonus Skills Experience with Apache Iceberg or similar table formats More ❯