3,276 to 3,300 of 8,327 Permanent Digital & IT Jobs

/interest in datastore technology such as MySQL and/or Cassandra. Hands‐on experience with public cloud platforms (we use AWS, but Azure/GCP are fine). Practical background in Infrastructure as Code and Configuration Management (e.g., Terraform, Puppet, Ansible, or similar). Relevant experience with ...

Adobe, Google, Facebook, TikTok, Twitter, LinkedIn. Commerce platforms such as Criteo, Profitero or Edge and Shopify. Foundational AI technology such as Mistral AI, Azure, AWS, LLaMa etc. CSR: We’re also focused on using tech to have a positive social impact. So, we’re working to reduce ...

TypeScript). Experience with distributed systems, RESTful/GraphQL APIs, system performance trade-offs, load balancing, and high availability engineering. Experience with AWS (Azure or GCP welcome), Infrastructure as Code (Terraform), CI/CD pipelines (e.g., GitLab), Docker, and Kubernetes. Experience with relational and NoSQL databases and automated ...

implementing software tools for engineering analysis, ideally within structural or defect tolerance applications.* Solid understanding of software development environments such as Python and Azure DevOps, with familiarity in tools such as Abaqus or Ansys.* Experience working across the full product lifecycle within a regulated industry, including knowledge ...

above or are eligible and willing to go through clearance You have experience working with security controls within cloud-based infrastructure (e.g Azure, AWS, GCP). This may include design, configuration, or protective monitoring. Knowledge of digital identity and authentication systems Experience applying data classification, handling requirements, data ...

above or are eligible and willing to go through clearance You have experience working with security controls within cloud-based infrastructure (e.g Azure, AWS, GCP). This may include design, configuration, or protective monitoring. Knowledge of digital identity and authentication systems Experience applying data classification, handling requirements, data ...

will likely bring experience in many of the following areas: Kubernetes platform engineering Cluster autoscaling and workload optimization Public cloud services (AWS, Azure or GCP) DevOps and CI/CD practices Site Reliability Engineering (SRE) FinOps and cloud cost management We are open to applications from experienced platform ...

modern service architectures Hands-on experience with Infrastructure as Code, particularly Terraform Experience designing and building distributed, asynchronous microservices using message brokers (e.g., Azure Service Bus, pub/sub). Knowledge of the insurance domain Core Values Love what you do: We show up each day ready ...

risks, and technical questions clearly and promptly. Pursue ongoing learning in cloud, data, IoT, and AI technologies. Preferred Qualifications Experience with OCI, AWS, Azure, Google Cloud, or another cloud platform. Experience with Kubernetes, Docker, microservices, distributed data systems, or event-driven architectures. Exposure to generative ...

risks, and technical questions clearly and promptly. Pursue ongoing learning in cloud, data, IoT, and AI technologies. Preferred Qualifications Experience with OCI, AWS, Azure, Google Cloud, or another cloud platform. Experience with Kubernetes, Docker, microservices, distributed data systems, or event-driven architectures. Exposure to generative ...

Waterfall project delivery methodologies. Desirable: Cloud Infrastructure: Hands-on experience with Google Cloud Platform (BigQuery, GCP storage) or equivalent cloud providers (AWS/Azure). Programming Languages: Proficiency in Python, R, or general-purpose scripting languages. Analytics Tools: Exposure to visualisation software (e.g., Looker, Looker Studio) and proficiency ...

such as PostgreSQL, modelling data, running ETL/ELT pipelines, and making pragmatic build-versus-buy calls. Experience deploying production systems in AWS, Azure or GCP, accounting for monitoring, secrets management, access control, backups and disaster recovery. Experience with production LLM pipelines: context engineering, evaluation, retrieval, tool ...

control, CI/CD, and the APIs that serve your own work. Hands-on with a major cloud and its managed AI services (Azure and AI Foundry, or the GCP/AWS equivalents), plus solid SQL and relational modelling. Architectural judgement: you make the design call, defend ...

GitOps and platform product management. Knowledge of SRE principles including SLOs, SLIs, and error budgets. Experience with multi-cloud infrastructure. Industry certifications in Azure, Kubernetes, Terraform, or cloud-native technologies. Core Competencies Platform Engineering Cloud-Native Architecture Developer Experience Kubernetes Operations Automation at Scale Infrastructure Engineering Reliability Engineering ...

analysis and resilience planning. Experience designing human‐in‐the‐loop decision tools (explainability, constraints override, auditability, and traceable recommendations). Cloud platform experience (Azure/AWS/GCP) and building secure, scalable services. Experience with event‐driven architectures, streaming, and near‐real‐time optimisation. Experience with data science ...

Agentic Systems: Experience designing and orchestrating autonomous agentic workflows (e.g., LangGraph) and managing agent state/memory. Cloud: Experience working with cloud infrastructure (Azure, AWS, or GCP). Agile Delivery: Experience working in an Agile development environment. Data Engineering: Proficiency in SQL and relational databases (e.g., PostgreSQL, DuckDB ...

with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Understanding of API development and integration. Familiarity with cloud platforms (e.g., AWS, Azure, or GCP) is a plus. Interest in RPA (Robotic Process Automation), data analytics, or low-code/no-code tools a bonus. Soft Skills ...

developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference ...

Experience translating business, operational, security and technical requirements into coherent end-to-end solution designs. Familiarity with modern technology ecosystems, including cloud platforms (Azure and AWS), APIs, containerisation, Kubernetes, event-driven architectures and COTS integrations. Experience producing architecture artefacts, integration views, data flow models and assurance documentation ...

pipelines using tools such as Jenkins or GitLab CI Performance optimisation (bundle size, lazy loading, rendering performance) Cloud platforms and static hosting (AWS, Azure or GCP) Observability tooling including logging, metrics and frontend monitoring Package management with npm, yarn or pnpm What Success Looks Like You’ll demonstrate ...

pipelines using tools such as Jenkins or GitLab CI Performance optimisation (bundle size, lazy loading, rendering performance) Cloud platforms and static hosting (AWS, Azure or GCP) Observability tooling including logging, metrics and frontend monitoring Package management with npm, yarn or pnpm What Success Looks Like You’ll demonstrate ...

plan and stay on top of output. Our target stack relies heavily on Python, containerisation, infrastructure as code, CI/CDand the Azure cloud. We work across the full spectrum of data sourcing and ETL to front‐end delivery. Projects areas include the front office and internal tooling. ...

pipelines using tools such as Jenkins or GitLab CI Performance optimisation (bundle size, lazy loading, rendering performance) Cloud platforms and static hosting (AWS, Azure or GCP) Observability tooling including logging, metrics and frontend monitoring Package management with npm, yarn or pnpm What Success Looks Like You’ll demonstrate ...

pipelines using tools such as Jenkins or GitLab CI Performance optimisation (bundle size, lazy loading, rendering performance) Cloud platforms and static hosting (AWS, Azure or GCP) Observability tooling including logging, metrics and frontend monitoring Package management with npm, yarn or pnpm What Success Looks Like You’ll demonstrate ...

developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference ...