10 of 10 Remote/Hybrid Prefect Jobs

DataOps Engineer delivering DataOps solutions in public sector or similarly regulated environments. Developing, orchestrating and maintaining data pipelines using tools like Airflow, Prefect, or Dagster. Containerising data applications using Docker and deploying them to Container Platforms (EKS, AKS and Kubernetes). Implementing CI/CD pipelines for data applications. Monitoring ...

grade data pipelines Solid understanding of integration patterns including REST APIs, webhooks, OAuth and event-driven architectures Experience with orchestration tools such as Airflow, Prefect or Dagster Familiarity with cloud environments (AWS, GCP or Azure) Experience with containerisation tools such as Docker and Kubernetes Proven experience integrating multiple business systems ...

This job is with Capgemini, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Who You Will Be Working With... ...

renowned for delivering mission-critical solutions, working with modern technologies in a secure, cutting-edge environment Key Skills required: - PyTorch - TensorFlow - SciKit - Airflow or Prefect - ML flow (really nice to have) - Python - SQL - Data Modelling This role will require an active SC Clearance and British Citizenship is required ...

SENIOR DATA ENGINEER£63,500 - Hybrid Working (2 days a week in office) - Bridgend, Wales. Your new company The company is a not-for-profit housing association established in 2003 as the first large-scale ...

premise, edge or customer-hosted environments. Monitoring, logging and production observability. Desirable Skills Kubernetes. MLflow, Weights & Biases or similar MLOps tooling. Airflow, Prefect, Kubeflow or other workflow orchestration tools. Time-series or telemetry data. Distributed training workloads. Industrial, IoT or edge computing environments. Why Join? Work on technically challenging machine ...

failures, data inconsistencies, and production issues Key Skills • Python & SQL (production-grade pipeline development) • REST APIs, webhooks, OAuth, event-driven architecture • Orchestration tools: Airflow, Prefect, or Dagster • Cloud platforms: AWS, GCP, or Azure • Docker & Kubernetes Microsoft 365 & Microsoft Copilot Desirable Skills • Vector databases and embedding pipelines • Real-time streaming (Kafka … production-grade data pipelines from scratch. • Deep familiarity with integration patterns: REST APIs, webhooks, OAuth, and event-driven architectures. • Experience with orchestration tools (Airflow, Prefect, or Dagster) and transformation frameworks (dbt or similar). • Comfortable across cloud platforms (AWS, GCP, or Azure) and with containerisation (Docker, Kubernetes). • Experience connecting ...

failures, data inconsistencies, and production issues Key Skills Python & SQL (production-grade pipeline development) REST APIs, webhooks, OAuth, event-driven architecture Orchestration tools: Airflow, Prefect, or Dagster Cloud platforms: AWS, GCP, or Azure Docker & Kubernetes Microsoft 365 & Microsoft Copilot Desirable Skills Vector databases and embedding pipelines Real-time streaming (Kafka … production-grade data pipelines from scratch. Deep familiarity with integration patterns: REST APIs, webhooks, OAuth, and event-driven architectures. Experience with orchestration tools (Airflow, Prefect, or Dagster) and transformation frameworks (dbt or similar). Comfortable across cloud platforms (AWS, GCP, or Azure) and with containerisation (Docker, Kubernetes). Experience connecting ...

failures, data inconsistencies, and production issues Key Skills Python & SQL (production-grade pipeline development) REST APIs, webhooks, OAuth, event-driven architecture Orchestration tools: Airflow, Prefect, or Dagster Cloud platforms: AWS, GCP, or Azure Docker & Kubernetes Microsoft 365 & Microsoft Copilot Desirable Skills Vector databases and embedding pipelines Real-time streaming (Kafka … production-grade data pipelines from scratch. Deep familiarity with integration patterns: REST APIs, webhooks, OAuth, and event-driven architectures. Experience with orchestration tools (Airflow, Prefect, or Dagster) and transformation frameworks (dbt or similar). Comfortable across cloud platforms (AWS, GCP, or Azure) and with containerisation (Docker, Kubernetes). Experience connecting ...

Data Science teams develop, train, deploy, monitor, and maintain machine learning models. Design, build, and maintain reusable ML infrastructure components using AWS services, Snowflake, Prefect, CI/CD pipelines, and other enterprise-grade tools. Provide technical leadership across ML engineering initiatives, ensuring solutions are robust, secure, scalable, observable, and aligned … infrastructure as code, containerisation, CI/CD, IaC, model versioning, and production monitoring. Support orchestration and automation of ML workloads using tools such as Prefect, AWS-native services, and event-driven patterns. Help define architectural standards and technical roadmaps for ML infrastructure, MLOps, AIOps, and GenAI capabilities. Review technical designs ...