23 of 23 Permanent Apache Airflow Jobs in the North West

Science or equivalent Experience in developing Finance or HR related applications Working experience with Tableau Working experience with Terraform Experience in creating workflows for Apache Airflow and Jenkins Benefits Roku is committed to offering a diverse range of benefits as part of our compensation package to support our More ❯

Services: Glue, Lambda, IAM, Service Catalogue, Cloud Formation, Lake Formation, SNS, SQS, Event Bridge Language & Scripting: Python and Spark ETL: DBT Good to Have: Airflow, Snowflake, Big Data (Hadoop), and Teradata Responsibilities: Serve as the primary point of contact for all AWS related data initiatives and projects. Responsible for More ❯

with big data technologies such as Hadoop, Spark, or Hive. Familiarity with data warehousing and ETL tools such as Amazon Redshift, Google BigQuery, or Apache Airflow. Proficiency in at least one programming language such as Python, Java, or Scala. Strong analytical and problem-solving skills with the ability to More ❯

for smooth deployments, ensuring platform stability and scalability through upgrades, and managing the data analytics platform. Responsibilities: Utilize modern data platform tools (dbt Core, Airflow, Airbyte, Snowflake, etc.). Collaborate with DevOps, Data Engineering, Infrastructure, and InfoSec for seamless application integration. Design, implement, and maintain scalable cloud data platform More ❯

for smooth deployments, ensuring platform stability and scalability through upgrades, and managing the data analytics platform. Responsibilities: Utilize modern data platform tools (dbt Core, Airflow, Airbyte, Snowflake, etc.). Collaborate with DevOps, Data Engineering, Infrastructure, and InfoSec for seamless application integration. Design, implement, and maintain scalable cloud data platform More ❯

for smooth deployments, ensuring platform stability and scalability through upgrades, and managing the data analytics platform. Responsibilities: Utilize modern data platform tools (dbt Core, Airflow, Airbyte, Snowflake, etc.). Collaborate with DevOps, Data Engineering, Infrastructure, and InfoSec for seamless application integration. Design, implement, and maintain scalable cloud data platform More ❯

for smooth deployments, ensuring platform stability and scalability through upgrades, and managing the data analytics platform. Responsibilities: Utilize modern data platform tools (dbt Core, Airflow, Airbyte, Snowflake, etc.). Collaborate with DevOps, Data Engineering, Infrastructure, and InfoSec for seamless application integration. Design, implement, and maintain scalable cloud data platform More ❯

for smooth deployments, ensuring platform stability and scalability through upgrades, and managing the data analytics platform. Responsibilities: Utilize modern data platform tools (dbt Core, Airflow, Airbyte, Snowflake, etc.). Collaborate with DevOps, Data Engineering, Infrastructure, and InfoSec for seamless application integration. Design, implement, and maintain scalable cloud data platform More ❯

communication and stakeholder management skills. Desirable: Experience working with large-scale retail datasets (e.g., POS, CRM, supply chain). Familiarity with tools like dbt, Airflow, or MLflow. Master’s or PhD in Data Science, Statistics, Computer Science, or related field. Benefits: Competitive salary and performance bonuses Flexible working options More ❯

communication and stakeholder management skills. Desirable: Experience working with large-scale retail datasets (e.g., POS, CRM, supply chain). Familiarity with tools like dbt, Airflow, or MLflow. Master's or PhD in Data Science, Statistics, Computer Science, or related field. Benefits: Competitive salary and performance bonuses Flexible working options More ❯

technical documentation Comfortable working with Agile, TOGAF, or similar frameworks Desirable: Experience with Python and data libraries (Pandas, Scikit-learn) Knowledge of ETL tools (Airflow, Talend, NiFi) Familiarity with analytics platforms (SAS, Posit) Prior work in high-performance or large-scale data environments Why Join? This is more than More ❯

technical documentation Comfortable working with Agile, TOGAF, or similar frameworks Desirable: Experience with Python and data libraries (Pandas, Scikit-learn) Knowledge of ETL tools (Airflow, Talend, NiFi) Familiarity with analytics platforms (SAS, Posit) Prior work in high-performance or large-scale data environments Why Join? This is more than More ❯

technical documentation Comfortable working with Agile, TOGAF, or similar frameworks Desirable: Experience with Python and data libraries (Pandas, Scikit-learn) Knowledge of ETL tools (Airflow, Talend, NiFi) Familiarity with analytics platforms (SAS, Posit) Prior work in high-performance or large-scale data environments Why Join? This is more than More ❯

technical documentation Comfortable working with Agile, TOGAF, or similar frameworks Desirable: Experience with Python and data libraries (Pandas, Scikit-learn) Knowledge of ETL tools (Airflow, Talend, NiFi) Familiarity with analytics platforms (SAS, Posit) Prior work in high-performance or large-scale data environments Why Join? This is more than More ❯

technical documentation Comfortable working with Agile, TOGAF, or similar frameworks Desirable: Experience with Python and data libraries (Pandas, Scikit-learn) Knowledge of ETL tools (Airflow, Talend, NiFi) Familiarity with analytics platforms (SAS, Posit) Prior work in high-performance or large-scale data environments Why Join? This is more than More ❯

technical documentation Comfortable working with Agile, TOGAF, or similar frameworks Desirable: Experience with Python and data libraries (Pandas, Scikit-learn) Knowledge of ETL tools (Airflow, Talend, NiFi) Familiarity with analytics platforms (SAS, Posit) Prior work in high-performance or large-scale data environments Why Join? This is more than More ❯

technical documentation Comfortable working with Agile, TOGAF, or similar frameworks Desirable: Experience with Python and data libraries (Pandas, Scikit-learn) Knowledge of ETL tools (Airflow, Talend, NiFi) Familiarity with analytics platforms (SAS, Posit) Prior work in high-performance or large-scale data environments Why Join? This is more than More ❯

more Key Responsibilities Develop and maintain ETL/ELT data pipelines using Python and SQL. Work with enterprise-level cloud platforms, ideally GCP (BigQuery, Airflow, Cloud Functions). Integrate APIs and process data from multiple sources. Design and optimise data warehouses and reporting systems. Build reports and dashboards using More ❯

Technical excellence across the Data Engineering ecosystem: We primarily work in python, go and SQL. Our code (tracked via github) deploys to GCP (Bigquery, Airflow/Composer, GKE, Cloud Run), dbt Cloud and Azure via terraform. We recognise this is a broad list; if youre not deeply familiar with More ❯

to architectural discussions and promote engineering best practices Technical Environment: Python, PyTorch or TensorFlow AWS (including SageMaker, S3, Lambda) or Azure ML Docker, Kubernetes, Airflow CI/CD tools (e.g. GitHub Actions, Jenkins) MLflow or similar frameworks Required Experience: Proven track record of deploying machine learning models to production More ❯

to architectural discussions and promote engineering best practices Technical Environment: Python, PyTorch or TensorFlow AWS (including SageMaker, S3, Lambda) or Azure ML Docker, Kubernetes, Airflow CI/CD tools (e.g. GitHub Actions, Jenkins) MLflow or similar frameworks Required Experience: Proven track record of deploying machine learning models to production More ❯

Flask, Django, or FastAPI. Proficiency in Python 3.x and libraries like Pandas, NumPy, and Dask. Experience with data manipulation and processing frameworks (e.g., PySpark, Apache Beam). Strong knowledge of databases, including SQL and NoSQL (e.g., PostgreSQL, MongoDB). Familiarity with ETL processes and tools such as Airflow More ❯

you be doing? Design and implement efficient ETL processes for data extraction, transformation, and loading. Build real-time data processing pipelines using platforms like Apache Kafka or cloud-native tools. Optimize batch processing workflows with tools like Apache Spark and Flink for scalable performance. Infrastructure Automation: Implement Infrastructure … Integrate cloud-based data services with data lakes and warehouses. Build and automate CI/CD pipelines with Jenkins, GitLab CI/CD, or Apache Airflow. Develop automated test suites for data pipelines, ensuring data quality and transformation integrity. Monitoring & Performance Optimization: Monitor data pipelines with tools like Prometheus More ❯