15 of 15 Remote Amazon S3 Jobs in the South East

Engineer: Design, build and maintain scalable data pipelines and architectures within the AWS ecosystem Leverage services such as AWS Glue, Lambda, Redshift, EMR and S3 to support data ingestion, transformation and storage Work closely with data analysts, architects and business stakeholders to translate requirements into robust technical solutions Implement

Site Reliability Engineering roles AWS Certification (Solutions Architect, DevOps Engineer, SysOps Administrator, or similar) with hands-on experience across core AWS services including EC2, S3, RDS, Route53, CloudFront, and ECS/EKS Infrastructure-as-Code proficiency with Terraform, CloudFormation, or similar tools Linux/Unix systems administration with strong

data analytics in Go or Python Handling real-time streaming data and batch pipelines Deploying containerised solutions to Kubernetes Working with AWS (EKS, EC2, S3) and Docker Writing clean, secure, test-driven code in an agile team Bonus experience (not essential): AI/ML concepts, Redis, Rust, Kafka/

following, or be open to learning: JavaScript: React, Node, Jest, Cypress Ruby (non-Rails environment) – nice to have AWS: EC2, ECS, Lambda, S3, SQS Databases: MongoDB & PostgreSQL They are looking for someone who is: Proactive, collaborative, and adaptable Approachable and supportive of colleagues A strong communicator with empathy

practices, processes and team culture. 2. Technical Foundations Experience with any of the following is beneficial (they are open-minded): Python AWS serverless (Lambda, S3, SQS, API Gateway) React/JavaScript REST APIs SQL Strong back-end or cloud developers from other stacks will still be considered. 3. Energy

will need to have skills and experience in the following: Cloud Data Architecture: Strong knowledge of modern, cloud-based data architecture and tooling (e.g., S3, Glue, Redshift, Athena, Lake Formation, Iceberg/Delta). AWS Platform Build: Demonstrable experience designing and building modern data platforms in AWS. ETL/

practices, processes and team culture. 2. Technical Foundations Experience with any of the following is beneficial (they are open-minded): Python AWS serverless (Lambda, S3, SQS, API Gateway) React/JavaScript REST APIs SQL Strong back-end or cloud developers from other stacks will still be considered. 3. Energy

scheduling, maintaining and resolving issues with batch or micro-batch jobs on AWS ETL or Azure ETL services Experience querying data stored on AWS S3 or Azure ADLSv2, or through a Lakehouse capability Experience in managing API-level and Database connectivity Experience using source control and DevOps tooling such

deliver changes. Technology Stack Full serverless cloud stack (AWS) SQL Database Python Back End Javascript/React Front End REST APIs AWS Facilities (S3/SQS/API Gateway/Lamdba) Qualifications Extensive experience of the Software Development Lifecycle Good experience of multi-tiered development via APIs Good experience

analytics engines (e.g. Spark/PySpark) and scripting languages such as Python or Scala. Hands-on use of cloud data stacks (e.g. SageMaker Notebooks, S3, Glue, Athena) and modern storage formats or frameworks (e.g. Parquet, Delta Lake, Fabric). Experience with DevOps/DataOps tooling and practices (e.g. Terraform

analytics (e.g. Spark/PySpark) Experience in writing, testing and implementing scripts (e.g. Python, Scala) Experience of cloud data stack use (e.g. SageMaker Notebooks, S3, Glue, Athena) Communicating technical concepts clearly to both technical and non-technical stakeholders using appropriate language and methods. Profiling data and analysing source systems

/VMware environments Manage backups & DR using Veeam Support networking: DNS, DHCP, VLANs, routing, VPN Assist with cloud technologies (M365, Intune, Google Apps, AWS S3) Work on infrastructure and migration projects Maintain documentation and deliver excellent customer service Technical Requirements Strong Windows Server & AD experience Hyper-V/VMware

technical requirements. Using SQL to analyse datasets, identify trends, validate assumptions, and support data-driven decisions. Working with AWS-based data platforms (e.g., S3, Redshift, Lambda, Glue) to support discovery, design and solution shaping. Mapping current and future-state processes, identifying gaps, inefficiencies, and opportunities for automation. Working with … data-driven or cloud-heavy environments. Hands-on SQL skills for querying, profiling, and analysing data. Practical exposure to AWS services (e.g., S3, Redshift, EC2, Lambda, RDS, Glue). Experience with data governance, information security, or privacy workflows. Knowledge of or direct involvement in Data Protection Impact Assessments (DPIAs

other related field Minimum 1 year working experience in Information Security, with proven focus in Cloud Security Deep technical knowledge of Amazon Web Services (AWS). Expertise … Microsoft Azure and Oracle Cloud will be considered an advantage Hands-on experience on AWS services such as IAM, Organizations, SSO, VPC, Transit Gateway, S3, EC2, RDS, ELB, CloudTrail, Config, Inspector, GuardDuty, WAF, etc Clear understanding of current threats to Cloud infrastructure and advanced knowledge of securing such environments

behavioural scientists, ML engineers, and analysts have the rocket fuel they need. What they'll actually do: Build rock-solid data pipelines across AWS (S3, Glue, Athena, Bedrock, OpenSearch) and Microsoft (Fabric, Power BI) Wrangle data from everywhere: RDS, MongoDB, HubSpot, S3 lakes—you name it Create