8 of 8 Amazon S3 Jobs in Scotland

Required Skills & Experience Cloud Testing (Mandatory) · Strong experience testing cloud-native platforms on AWS . · Hands-on experience with services such as: o AWS S3 o Lambda o Glue o EMR o ECS/EKS o RDS o IAM o CloudWatch · Understanding of cloud architecture, distributed systems, and microservices. ...

state, workspace/environment management, and change management workflows Solid experience with core AWS services relevant to cloud data platforms, such as VPC, IAM, S3, EC2/ECS/EKS, RDS, KMS, CloudWatch, and load balancing Working experience with Databricks, including platform administration and/or building and supporting ...

Java, including experience building and maintaining large-scale, production-grade applications Hands-on experience designing and deploying cloud-native solutions on AWS (e.g., EC2, S3, Lambda, RDS, EKS) Demonstrated experience building and maintaining CI/CD pipelines using industry-standard tools Strong understanding of software design patterns, distributed systems ...

Factory, Informatica, or similar.Hands-on experience with major cloud platforms (AWS, Azure, or GCP) including Snowflake deployment, networking (Private Link), and cloud storage integration (S3, ADLS, GCS); familiarity with lakehouse stacks (Databricks, Delta Lake, Apache Iceberg) is a plus.Mastery of Snowflake security and governance: RBAC, tag-based governance, dynamic ...

engineering practices. Improving testing, deployment pipelines, monitoring and documentation. Technology Stack PHP/Laravel TypeScript, Node.js, NestJS React MySQL & PostgreSQL AWS (Lambda, ECS, RDS, S3, SQS, SNS) Docker & CI/CD pipelines Monitoring and observability tools What We're Looking For Strong experience in either PHP/Laravel ...

Strong awareness of risk, controls, testing, documentation, and technology, security, and change standards. Desirable Skills/Preferred Qualifications Experience with Starburst/Trino, AWS S3 concepts, and distributed query behavior for large-dataset validation and troubleshooting. Exposure to React JS or API-driven operational user interfaces for configuration, monitoring ...

agents across client platforms Architect and implement RAG pipelines using Amazon Bedrock Knowledge Bases, managing vector stores, embeddings, and document ingestion from S3 and other sources Apply the A2A (Agent-to-Agent) protocol to enable interoperability between agents across systems and workflows Instrument AI systems with observability … compliance requirements Integrate LLMs into client applications through prompt engineering, context management, and function/tool calling patterns Leverage serverless infrastructure — AWS Lambda, DynamoDB, S3 — to build scalable, cost-efficient backends for AI workloads Collaborate with client engineering and product teams to translate requirements into agent architectures, contributing ...

Build and maintain the batch and ELT pipelines the ML work sits on, using Python, PySpark, and cloud data services (e.g., AWS Glue, EMR, S3, Redshift, Athena, or the Databricks/Snowflake equivalents), making sound decisions on architecture, data modelling, and tooling and weighing up trade-offs in performance … person designing the model Have designed and operated production data pipelines on a modern cloud data platform, AWS (Glue, EMR, Redshift, S3/Lake Formation), Databricks, Snowflake or comparable, and can talk about which of those decisions would travel to a different one, and which wouldn’t Have deep ...