1,501 to 1,525 of 5,433 Permanent AWS Jobs

automation for improved efficiency and security. Requirements: Commercial hands-on experience working on DevOps projects ideally in a start-up or scale-up environments Proficiency with: Linux, Docker, Python, AWS, Azure DevOps, and Automation/Scripting Degree level education or significant commercial experience in the software industry Excellent communication skills, with the ability to explain complex technical concepts This company More ❯

service management. Participate in continuous improvement initiatives and tooling exploitation to enhance operational efficiency. Required Skills and Experience Strong understanding of IT infrastructure (Windows, Unix, Linux) and cloud platforms (AWS, Azure). Hands-on experience with monitoring tools such as Splunk, Splunk ITSI, Dynatrace, AppDynamics, and synthetic monitoring platforms. Familiarity with enterprise systems such as WebLogic, Apache, Oracle, and SQL. More ❯

to write and review YAML or JSON-based Swagger files manually or using tools (e.g., SwaggerHub, Postman, Stoplight). Familiarity with API management platforms (e.g., Apigee, Azure API Management, AWS API Gateway). Understanding of HTTP methods, response codes, and common API security practices (OAuth, JWT, etc.). Excellent communication skills to interact with both business users and technical teams. More ❯

of software architecture and engineering principles Experience with Agile methodologies (Scrum, Kanban, etc.) Familiarity with modern development stacks (e.g., .NET, Java, Python, or similar) Experience with cloud platforms (e.g., AWS, Azure) and DevOps practices Excellent leadership, communication, and stakeholder management skills Whats on Offer: Competitive salary: £60,000 £80,000 (depending on experience) Performance and annual bonus scheme Hybrid working More ❯

service management. Participate in continuous improvement initiatives and tooling exploitation to enhance operational efficiency. Required Skills and Experience Strong understanding of IT infrastructure (Windows, Unix, Linux) and cloud platforms (AWS, Azure). Hands-on experience with monitoring tools such as Splunk, Splunk ITSI, Dynatrace, AppDynamics, and synthetic monitoring platforms. Familiarity with enterprise systems such as WebLogic, Apache, Oracle, and SQL. More ❯

Engineering Team Support: Demonstrated experience managing end user accounts, permissions, access rights, and storage allocations in accordance with best practices. Demonstrated experience installing and managing cloud-based applications in AWS, Azure, or GCP. Demonstrated experience with Kubernetes and containerization. Demonstrated experience performing software and hardware upgrades, patches and reconfigurations. Demonstrated experience managing the physical environment of server racks including cable More ❯

using DDD and other architectural approaches across an event-driven modular monolith , Shape and evolve our architecture as we transition from Java to Node.js/TypeScript in a modern AWS-based environment , Work closely with product and operations to build features that serve both external users and internal teams , Play a key role in refactoring and rearchitecting complex codebases, balancing More ❯

Elasticsearch/Spark/Hadoop/PostgreSQL) Infrastructure Management - CasC, IasC (Ansible, Terraform, Packer) Log and metric aggregation with Fluentd, Prometheus, Grafana, Alertmanager Public Cloud, primarily GCP, but also AWS and Azure More ❯

First experiences in programming languages such as Java, C# or Go Basic knowledge in backend development (APIs, databases, etc.) Familiarity with cloud computing concepts and technologies, like MS Azure, AWS, GCP, containerization and Kubernetes Motivated and enthusiastic about working in an agile team environment Profound communication skills in both German and English Our offer At the Liebherr Digital Development Center More ❯

in languages such as Python, SQL, or Java. Familiarity with data processing frameworks and tools (e.g., Apache Spark, Hadoop, Kafka) is a plus. Basic understanding of cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services. Knowledge of database systems (e.g., MySQL, PostgreSQL, MongoDB) and data warehousing concepts. Excellent problem-solving skills and a keen attention to detail. Strong More ❯

and knows how to balance strategy with delivery. Proven background leading engineering teams of 30+ in complex environments Experience scaling engineering functions in a cloud-first or SaaS business (AWS preferred) Strong grasp of modern development practices (CI/CD, IaC, microservices, containerisation, etc.) Adept at fostering high-performing product engineering cultures, especially through periods of change or growth Experience More ❯

and knows how to balance strategy with delivery. Proven background leading engineering teams of 30+ in complex environments Experience scaling engineering functions in a cloud-first or SaaS business (AWS preferred) Strong grasp of modern development practices (CI/CD, IaC, microservices, containerisation, etc.) Adept at fostering high-performing product engineering cultures, especially through periods of change or growth Experience More ❯

and knows how to balance strategy with delivery. Proven background leading engineering teams of 30+ in complex environments Experience scaling engineering functions in a cloud-first or SaaS business (AWS preferred) Strong grasp of modern development practices (CI/CD, IaC, microservices, containerisation, etc.) Adept at fostering high-performing product engineering cultures, especially through periods of change or growth Experience More ❯

take ownership, move fast, and know when to bring others in You communicate clearly - sharp thinking, no hand-holding needed Our stack: TypeScript, React, Python, a bit of Rust, AWS with a bunch of monitoring tools sprinkled in. The latest web3 tools as standard foundry, rainbowkit, wagmi, viem, etc. We keep it simple and don't employ elaborate systems where More ❯

architectures (Kafka, Confluent). Experience with data lakes/lakehouses (Databricks, Unity Catalog). Familiarity with Data Mesh, Data Fabric, and product-led data strategies. Expertise in cloud platforms (AWS, Azure, GCP, Snowflake). Technical Skills Proficiency in big data tools (Apache Spark, Hadoop). Programming knowledge (Python, R, Java) is a plus. Understanding of ETL/ELT, SQL, NoSQL More ❯

Description, please Click Here Who we are looking for: You have strong SQL and Python skills, solid data engineering fundamentals, and experience delivering pipelines in a cloud environment (Azure, AWS, or GCP). Experience with Azure Data Factory, Synapse, or Data Lake Gen2 is beneficial, as is exposure to Databricks, Delta Lake, Iceberg, CI/CD, Power BI, or middleware More ❯

MARL approaches • Experience with reinforcement learning, human feedback, and related system learning methods • Experience creating and deploying containerized AI models with Docker/Kubernetes • Working with cloud AI platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI) • Experience with model monitoring, A/B testing, and performance optimization • Experience with real-time inference systems and low-latency model serving • Knowledge of More ❯

as part of foundational work. Essential Skills Proven experience as a Senior or Lead Data Engineer in complex, agile environments. Strong proficiency in Airflow (or similar orchestration tools), Snowflake, AWS, Python, and SQL. Excellent problem-solving skills and ability to work with incomplete or evolving information. Strong communication and interpersonal skills; able to work independently and take initiative. Additional Skills More ❯

experience, committing code to a production environment. Proficiency in large-scale data processing (e.g. Spark, Cloud SQL ), and large-scale data systems (Iceberg, Parquet, ) Proficiency in cloud platforms (e.g. AWS, GCP, Azure). Proficiency in the Python ecosystem and its best practices Experience in CI/CD (e.g. CircleCI). Preferred Qualifications Familiarity and enthusiasm about AI-based coding solutions More ❯

including the use of Continuous Integration/Continuous Delivery (CI/CD) Tooling (Git runners, code scanning tools). Experience operating in cloud based development and production environments (prefer AWS) Familiarity with Object Relational Modeling persistence frameworks (e.g. SQLAlchemy), and with PostgreSQL. Strong communications skills to collaborate with team and customers Ability to synthesize requirements underlying feature requests, recommend alternative More ❯

would include data mesh, data orchestration, control gates review, and vulnerability management within a pipeline Expansive knowledge with integrating IaaS, PaaS, and SaaS offerings into government cloud environments (ie. AWS, AZURE & GCP) Experience would include cloud compute, cloud storage, cloud native solutions, cloud data transfer, cross domain solutions, and cloud networking Experience assessing STIGs, cloud compliance guides, Shares responsibility models More ❯

VectorDBs). Backend development using Python. Software development lifecycle using Git, Agile, and test-driven development. Docker/Kubernetes containerisation and CI/CD pipelines. Additional valued skills include: AWS implementation experience using IaC and best practices (EC2, EKS, GPUs, SageMaker, RDS). Curious engineers with good collaborative skills. Data engineering experience with frameworks like Airflow, DBT, Spark. Bachelor's More ❯

a focus on knowledge continuity and internal capability uplift. PERSONAL PROFILE Proven experience as a Principal or Staff Engineer in a cloud-native environment, ideally with strong exposure to AWS (Lambda, Fargate, CDK/Terraform, etc.). Deep backend engineering knowledge, particularly using Node.js or similar, with strong CI/CD experience (e.g. GitLab, Snyk). Demonstrated ability to work More ❯

data structures and algorithms for efficient problem-solving. Experience with version control systems like Git and familiarity with branching strategies and code review practices. Familiarity with cloud infrastructure, particularly AWS, and experience in deploying and managing applications in cloud environments. Understanding of DevOps practices, CI/CD pipelines, and the ability to leverage automation tools to streamline the software development More ❯

discovery. Provide software development support to the ML model life cycle, working in the design and development of: Efficient and maintainable data pipelines Benchmarking systems of models Deployments to AWS and use of Kubernetes (in collaboration with our cloud engineers) Collaborate on the creation, testing and maintenance of software systems Code review for pull requests in adjoining areas Maintenance of More ❯