9 of 9 Prefect Jobs in London

. Proficiency in Python and SQL for data manipulation and transformation. Experience with ETL/ELT development and orchestration tools (e.g., Apache Airflow, dbt, Prefect). Knowledge of data modelling, data warehousing, and lakehouse architectures. Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code. Strong problem-solving ...

Weaviate, FAISS, Milvus) Data & Engineering Excellence Lead the evolution of modern data platforms (Databricks, Snowflake, Synapse, BigQuery) Ensure robust data engineering practices (Airflow, dbt, Prefect) and governance (Collibra, Purview) Drive scalable lakehouse architectures (Delta Lake, Iceberg, Hudi) Cloud, Infrastructure & MLOps Champion multi-cloud engineering across Azure, AWS, and GCP Lead ...

across the stack — they love new ideas What You Bring Hands-on experience in Python and SQL Experience with modern data tools (dbt, Airflow, Prefect, Dagster, etc.) Knowledge of cloud platforms like AWS , GCP , or Azure An understanding of data modelling and ETL best practices Curiosity, creativity, and a mindset ...

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 ...

solutions meet business needs. Experience with data ingestion tools, like Fivetran. Advantageous Exposure to deploying applications with Kubernetes. Experience with Data Orchestrator tools (Airflow, Prefect, etc.). Experience with Data Observability tools (Montecarlo, Great Expectations, etc.). Experience with Data Catalog tools (Amundsen, OpenMetadata, etc.). Benefits Winning team ...

distributed compute, GPU optimization, and MLOps architecture. Willingness to learn new parts of the ML tech stack – Python, PyTorch, Docker, Kubernetes, Ray, Weights & Biases, Prefect, BigQuery, Postgres, GCP, CUDA, and model serving frameworks. Fluency in life sciences or drug discovery is a plus. Working Location & Compensation: This is an office ...

creating. You'll have experience with: AWS and cloud-native technologies Snowflake or similar cloud data platforms Data orchestration tools such as Airflow, Prefect or similar Amazon S3 and modern data architectures Postgres and semi-structured data models Event-driven architectures and scalable systems You'll understand how data enters ...

sensor/energy/building data Python (NumPy, pandas, scikit-learn, etc.) Productionisation of models into scalable workflows MLOps practices (e.g. MLflow, Airflow/Prefect, Docker) Building reproducible, well-tested data science pipelines Working with noisy, real-world operational datasets Strong model evaluation, monitoring and deployment practices 📈 What Success Looks ...

across multiple regions. Technical Environment Experience across some of the following technologies is advantageous: AIops and enterprise automation frameworks Workflow orchestration platforms (Airflow, Argo, Prefect) Configuration and automation tools (Ansible, Salt, Puppet) ITSM and ITOM platforms Event-driven automation and runbook-as-code approaches Messaging technologies such as Kafka ...