17 of 17 Apache Airflow Jobs in Berkshire

maintain scalable, cloud-based data pipelines and architectures to support advanced analytics and machine learning initiatives. Develop robust ELT workflows using tools like dbt, Airflow, and SQL (PostgreSQL, MySQL) to transform raw data into high-quality, analytics-ready datasets. Collaborate with data scientists, analysts, and software engineers to ensure … however Azure exposure is essential. Data Warehousing: Proven expertise with Snowflake – schema design, performance tuning, data ingestion, and security. Workflow Orchestration: Production experience with Apache Airflow (Prefect, Dagster or similar), including authoring DAGs, scheduling workloads and monitoring pipeline execution. Data Modeling: Strong skills in dbt, including writing modular ...

schema). Version Control Practical experience with Git (branching, merging, pull requests). Preferred Qualifications (A Plus) Experience with a distributed computing framework like Apache Spark (using PySpark). Familiarity with cloud data services (AWS S3/Redshift, Azure Data Lake/Synapse, or Google BigQuery/Cloud Storage … . Exposure to workflow orchestration tools (Apache Airflow, Prefect, or Dagster). Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field. ...

governance, and data architecture. Familiarity with modern data architectures and cloud-based/distributed systems. Proficiency in SQL, Python and data pipeline tools (e.g., Apache Airflow, Spark). Experience working with major cloud platforms (AWS, Azure, GCP) and big data technologies. Awareness of data governance, data sharing across ...

frameworks such as React or Next.js. Experience creating and maintaining APIs, working with relational/non‐relational databases. Familiarity with data orchestration tools (e.g. Airflow) and data warehouse/lake design. Practical knowledge of AWS or Azure cloud environments. Strong understanding of Git, CI/CD, and modern deployment ...

environment looks a bit like this Python (pandas, numpy, scipy, PySpark) SQL AWS or GCP (BigQuery/RedShift/Snowflake) Spark/Databricks Airflow/Dagster ...

cloud technologies. You will be utilising and playing with tools across the entire data ecosystem. Essential tech skills include proficiency in Python, Spark, and Airflow, alongside experience with major data platforms such as Snowflake, Databricks, and BigQuery. Familiarity with data transformation and infrastructure as code tools like dbt, Fivetran ...

have indepth technical knowledge of Python for data workflows, SQL and Data Modelling, DBT, Cloud platforms (AWS, GCP or Azure), Workflow Orchestration tools (e.g. Airflow, Dagster, Prefect, DBT Cloud), CI/CD (GitHub Actions, GitLab CI, CircleCI) You have experience of leading technical deployments, running customer projects, diagnosing issues ...

another language e.g. Python ELT/ETL CI/CD Data Modelling Data Architecture Data Frameworks dbt Data processing and orchestration using Airflow or similar Google BigQuery or Redshift Cloud based services: GCP (preferred) or AWS Agentic development frameworks Automations About You 6 years+ experience as a Data Engineer ...

working as a Data Engineer or in a similar data-focused engineering role Strong Python and SQL skills Experience building and orchestrating data pipelines (Airflow or similar tools) Hands-on work with cloud platforms (AWS and/or Azure) Solid understanding of databases, data warehouses, and data lakes Experience ...

including Azure DevOps or GitHub Considerable experience designing and building operationally efficient pipelines, utilising core Cloud components, such as Azure Data Factory, Big Query, AirFlow, Google Cloud Composer and Pyspark etc Proven experience in modelling data through a medallion-based architecture, with curated dimensional models in the gold layer ...

Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35) Initial 6-month contract, with ...

tech firm Strong hands-on expertise in Python and modern ETL frameworks Experience designing and maintaining cloud-based data pipelines (e.g. AWS, Airflow, Snowflake) Deep understanding of data modelling, validation, and pipeline resilience Familiarity with financial or alternative datasets preferred ...

growth, including Agentic development. Technology/Skills requirements SQL ELT/ETL Data Modelling dbt models Version control (Git) Data processing and orchestration using Airflow or similar Google BigQuery or Redshift Cloud based services: GCP (preferred) or AWS Agentic development frameworks Automations About You 4 years+ experience ...

designing and owning data and analytics platforms in cloud environments. Dealing with huge volumes of data in a modern stacks (e.g. Snowflake, dbt, Airflow) and CI/CD practices. Whilst having microservices experience within a cloud environment, ideally AWS. If you have domain experience, great ...

technologies including the Python scientific stack (NumPy, Pandas, SciPy, etc.), frameworks such as OpenCV, PyTorch, TensorFlow and JAX, data pipeline tools such as Airflow or Prefect and data processing tools such as Spark or Databricks. The Company The Python Developer will be joining a company whose platform has been ...

programming skills in Python; experience with ML libraries such as Snowpark, PySpark, or PyTorch Experience with containerization tools like Docker and orchestration tools like Airflow or Astronomer Familiarity with cloud platforms (AWS, Azure) and ML services (e.g., SageMaker, Vertex AI) Experience with CI/CD pipelines and automation tools ...

Design and implement model registries, versioning systems, and experiment tracking to ensure full reproducibility of all model releases. Deploy ML workflows using tools like Airflow or similar, managing dependencies from data ingestion through model deployment and serving. Instrument comprehensive monitoring for model performance, data drift, prediction quality, and system ...