1 to 25 of 137 Observability Jobs in Scotland

eliminate platform bottlenecks. Define and promote paved paths and self-service workflows for developers. Implement real-time telemetry pipelines and workflows for platform observability and analytics. Champion adoption of productivity tools through documentation, training, and engagement with the developer community. Standardize use of AI-assisted coding tools and AI-powered ...

eliminate platform bottlenecks. Define and promote paved paths and self-service workflows for developers. Implement real-time telemetry pipelines and workflows for platform observability and analytics. Champion adoption of productivity tools through documentation, training, and engagement with the developer community. Standardize use of AI-assisted coding tools and AI-powered ...

eliminate platform bottlenecks. Define and promote paved paths and self-service workflows for developers. Implement real-time telemetry pipelines and workflows for platform observability and analytics. Champion adoption of productivity tools through documentation, training, and engagement with the developer community. Standardize use of AI-assisted coding tools and AI-powered ...

issues and partnering with development teams to resolve them. Maintain and monitor asset inventory across environments. Monitor, troubleshoot, and remediate issues using Splunk and observability/monitoring platforms such as Datadog, Dynatrace, or Grafana. Support cost rationalization efforts; partner with architects to gather, clarify, and translate technical requirements. Proficient with ...

Agentic AI in a ELT/ETL capacity (Preferred) Exposure to Kafka or streaming platforms from an infrastructure or operational perspective (Preferred) Experience with observability tooling (logging, metrics, alerting) for cloud platforms (Preferred) Understanding of FinOps, cost optimisation, and capacity management in AWS (Preferred) Familiarity with data governance tooling such ...

along with good understanding of REST APIsHands-on experience with cloud-based technologies and tools especially in deployment, monitoring and operations, such as Google Observability, Azure Monitor, Data Dog, Prometheus, Splunk, Elasticsearch and Grafana. Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve SRE workflows (e.g. ...

with good understanding of REST APIs Hands-on experience with cloud-based technologies and tools especially in deployment, monitoring and operations, such as Google Observability, Azure Monitor, Data Dog, Prometheus, Splunk, Elasticsearch and Grafana. Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve SRE workflows (e.g. ...

drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture. Drives continuous improvement in system observability, alerting, and capacity planning. Collaborates with engineering and data teams to optimize infrastructure and deployment processes, focusing on automation and operational excellence. Performs platform design ...

Cloud platforms (AWS, Azure or GCP CI/CD pipelines using tools such as Jenkins or GitLab CI Git and modern software development workflows Observability tooling including logging, metrics and distributed tracing Comprehensive testing across unit, integration and functional layers Maven or Gradle Java concurrency and JVM performance fundamentals Experience ...

Data: Proficiency with Docker, Kubernetes, and relational databases (MS SQL, Sybase). Delivery Automation & Monitoring: Strong focus on automated testing, automated release pipelines, and observability tools (Grafana, Prometheus). Mindset: Delivery-focused problem solver with a hands-on approach and strong stakeholder communication skills. Desirable Experience Background in Equity Swaps ...

depth in disciplines such as cloud, AI/ML, or data engineering Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal) Advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance ...

depth in disciplines such as cloud, AI/ML, or data engineering Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal) Advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance ...

depth in disciplines such as cloud, AI/ML, or data engineering Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal) Advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance ...

more of AWS, Azure and/or GCPAutomation & IaC: Terraform, Ansible, Puppet; CI/CD pipelines (Jenkins, GitHub Actions).Observability & Monitoring: Experience integrating observability and monitoring solutions (Splunk, Prometheus, Loki, Grafana).AI & Advanced Analytics Exposure: LLM Integration: Retrieval-augmented generation, fine-tuning, prompt engineering. Generative AI: Building and deploying generative ...

Kernel, and related ecosystems. Experience building and scaling enterprise AI platforms, ML infrastructure, and intelligent applications serving thousands of users. Strong understanding of model observability, monitoring, evaluation frameworks, experimentation, reliability, and operational perfection. Expertise in cloud-native AI development using Azure AI Foundry, Azure Machine Learning, Azure OpenAI, Azure ...

expertise in Go and/or Python Kubernetes platform engineering experience, including CRDs and API extensions. Strong knowledge of Kubernetes internals, multi-tenancy and observability Proven experience with CI/CD, automation, infrastructure as code and deployment pipelines. Strong understanding of SDLC, Agile delivery, resiliency and security Practical ...

expertise in Go and/or Python Kubernetes platform engineering experience, including CRDs and API extensions. Strong knowledge of Kubernetes internals, multi-tenancy and observability Proven experience with CI/CD, automation, infrastructure as code and deployment pipelines. Strong understanding of SDLC, Agile delivery, resiliency and security Practical ...

with depth in disciplines such as cloud, AI/ML, or data engineeringExperience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal)Advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governancePractical ...

products through code reviews, technical design, and pairing with peers and junior engineersEstablishes and operates Responsible AI controls in production (guardrails, evaluation frameworks, observability, and model risk controls) to firm-wide standardsActs as a primary technical partner to IPB business stakeholders, surfacing new AI/ML opportunities and shaping them ...

Fluency in Python & deep knowledge of software applications and technical processes with emerging depth in one or more technical disciplines Proficiency and experience in observability such as white and black box monitoring, SLO alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, etc. Proficiency in continuous ...

RabbitMQ Docker and containerised application development CI/CD pipelines using tools such as Jenkins or GitLab CI Git and modern software development workflows Observability tooling including logging, metrics and distributed tracing Comprehensive testing across unit, integration and functional layers Maven or Gradle Java concurrency and JVM performance fundamentals Experience ...

with depth in disciplines such as cloud, AI/ML, or data engineeringExperience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal)Advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governancePractical ...

Bring Significant commercial experience in software engineering and technical leadership. Strong knowledge of cloud-native development, CI/CD, infrastructure as code, automated testing, observability and secure software development. Practical experience with AWS, GitLab or comparable platforms, APIs, containers and modern programming languages. Experience coaching and mentoring teams with different ...

Bring Significant commercial experience in software engineering and technical leadership. Strong knowledge of cloud-native development, CI/CD, infrastructure as code, automated testing, observability and secure software development. Practical experience with AWS, GitLab or comparable platforms, APIs, containers and modern programming languages. Experience coaching and mentoring teams with different ...

also be useful. We're particularly interested in people who have worked with modern data platforms and understand the principles of ELT, automation, testing, observability, data quality and infrastructure-as-code . What You'll Bring A strong understanding of modern data engineering practices A genuine interest in building well ...