10 of 10 Contract Amazon RDS Jobs in England

with Python or Bash. Modern CI/CD practices and pipeline creation (e.g., Jenkins, GitHub Actions). Infrastructure as Code tools (Terraform), configuration management (Ansible preferred). Aurora/RDS MySQL (including replication). Monitoring/logging tools (Datadog, Sumo Logic, etc.). Security best practices (server hardening, 2FA, secure data storage). Solid understanding of networking concepts: routing More ❯

with Python or Bash. Modern CI/CD practices and pipeline creation (e.g., Jenkins, GitHub Actions). Infrastructure as Code tools (Terraform), configuration management (Ansible preferred). Aurora/RDS MySQL (including replication). Monitoring/logging tools (Datadog, Sumo Logic, etc.). Security best practices (server hardening, 2FA, secure data storage). Solid understanding of networking concepts: routing More ❯

/CentOS) and scripting with Bash, Python, or Go Significant experience with AWS cloud infrastructure Deep understanding of IaC tools: Terraform, Packer, CloudFormation. Expereince of administering MongoDB clusters or RDS (not just used as a developer). Strong Terraform experience including production managing modules, remote state, multi-env, or Terragrunt. Understanding of version control, state backends, and team collaboration More ❯

Strong expertise in Java 8, microservices, event-driven systems. Kafka – production clusters, consumer lag, scaling, tuning, troubleshooting. MongoDB – replication, sharding, performance tuning, backups/restores. AWS – EC2, VPC, S3, RDS, IAM, ALB/NLB; HA design and cost optimisation desirable. Terraform – production experience (modules, remote state, multi-env, collaboration). Linux administration – CLI tools, system performance, network debugging, patching. More ❯

Professional Technical knowledge and experience across various IT areas, including infrastructure, automation development, and operations Troubleshoot and configure core AWS Platforms such as ECS Fargate, Lambda, S3, Route 53, RDS, etc. Administer software-defined networking in AWS, proficient in managing NACL's and AWS Security Groups. Ability to automate processes/code in Python, or another modern scripting language More ❯

MongoDB – strong admin experience including replication, sharding, tuning, and backups. Monitoring/Observability – Prometheus, Grafana, ELK, Datadog, with strong alerting/SLO design. AWS – expertise across EC2, VPC, S3, RDS, IAM, ALB/NLB, and cost optimisation. Linux – advanced administration, performance debugging, and security hardening. CI/CD & Automation – Jenkins, GitLab CI, or GitHub Actions, plus containerisation (Docker/ More ❯

strong cloud experience is essential. Tech Stack: Front End: React, Next, HTML5, CSS3 Back End: Python (FastAPI/Flask/Django) Cloud: AWS (EC2, Lambda, S3, CloudFormation/CDK, RDS, etc.) CI/CD & DevOps: GitHub Actions, Docker, Terraform Testing: Jest, React Testing Library, Pytest What You'll Be Doing: Building intuitive, responsive, and accessible UIs using React and More ❯

and ETL processes for capital markets data Hands-on experience with AWS cloud services and Snowflake data platform Experience with cloud-native development patterns and AWS services (Lambda, S3, RDS, etc.) Hands-on experience integrating with OMS platforms (Aladdin, Murex, Charles River, etc.) including data extraction, transformation, and real-time feeds Strong understanding of the capital markets trade lifecycle More ❯

solving and communication skills Solid understanding of software engineering principles (testing, version control, CI/CD) Nice to Have Experience with AWS services such as Glue, Aurora, S3, and RDS Ability to design and optimize schemas for structured and semi-structured data Familiarity with authentication protocols (OAuth2, API keys) Experience working with highly diverse datasets in technically complex environments More ❯

ML engineers to reduce time-to-production for experiments and prototypes. Design and optimize data wrangling and transformation workflows using Python. Leverage AWS cloud services (EC2, S3, Lambda, SageMaker, RDS, DynamoDB, Redshift, etc.) to build robust, scalable, and cost-effective solutions. Apply AIOps practices to enhance monitoring, automation, and resilience of ML systems. Implement best practices in data engineering … role. Strong background in data structures, algorithms, and software engineering principles. Advanced proficiency in Python for data wrangling, pipeline automation, and ML workflows. Expertise in AWS services, including databases (RDS, DynamoDB, Redshift) and machine learning/AI (SageMaker, AI/ML frameworks). Hands-on experience with ML pipeline orchestration, CI/CD, and deployment automation. Deep understanding of More ❯