6 of 6 Apache Airflow Jobs in Guildford

Vertex AI or Azure ML Data engineering and MLOps Experience with data warehouses such as Snowflake, BigQuery or Redshift Workflow orchestration using tools like Airflow or Dagster Experience with MLOps tools such as MLflow, Weights and Biases or similar Awareness of data and model drift, and how to monitor ...

Organization. Technologies used on the team include: Languages: Go, Python, Scala Frameworks: Spark, Thrift, Kafka Data stores: Postgres, BigQuery, Redis, Druid Tools: Kubernetes, Airflow, Docker Job responsibilities: You will work with the existing engineering team and help contribute to the direction of the projection and team Collaborate with cross ...

start-ups or high-growth scale-ups • Strong technical grounding across Node.js, Typescript, React, MySQL and cloud-native architectures (AWS, ECS/K8s, Kafka, Airflow) • Comfortable driving Agile and DevOps culture, and setting high standards for clean, testable, secure code in fast-moving environments If you want ...

resilience and data residency Confidence working with senior stakeholders to make pragmatic, commercial platform decisions Tech environment includes: AWS, Azure, Kubernetes (EKS), ECS, Terraform, Airflow, EFK/Prometheus/Grafana, MySQL/PostgreSQL/Redis/Elasticsearch/Kafka, GitHub Actions, plus services written in Python, Node.js and Go. ...

team to make sure our data function not only delivers but also drives strategic decision-making. Our Tech Stack: Python, Docker, Dagster, dbt, Fivetran, Apache Iceberg, Snowflake, S3, Glue, ECS, and Omni. We're constantly evolving our stack and welcome input from engineering leaders on how we can improve … scaling data platforms in a high-growth or start-up environment. Strong expertise in Python and SQL, with deep experience in orchestration frameworks (Dagster, Airflow, Prefect). Advanced knowledge of data modelling and architecture (Kimball dimensional modelling, Data Vault etc). Hands-on experience with dbt, modern data warehouses ...

fast-paced, challenging environment. Key Responsibilities: Design, implement, and debug ETL pipelines to process and manage complex datasets. Leverage big data tools, including Apache Kafka, Spark, and Airflow, to deliver scalable solutions. Collaborate with stakeholders to ensure data quality and alignment with business goals. Utilize programming expertise … data engineering projects Good hands-on experience of designing, implementing, debugging ETL pipeline Expertise in Python, PySpark and SQL languages Expertise with Spark and Airflow Experience of designing data pipelines using cloud native services on AWS Extensive knowledge of AWS services like API Gateway, Lambda, Redshift, Glue, Cloudwatch, etc. ...