22 of 22 Permanent Apache Airflow Jobs in Manchester

object-oriented design principles, and data structures Extensive experience in developing microservices using Java, Python Experience in distributed computing frameworks like - Hive/Hadoop, Apache Spark. Good experience in Test driven development and automating test cases using Java/Python Experience in SQL/NoSQL (Oracle, Cassandra) database design … following cloud services: AWS Elastic Beanstalk, EC2, S3, CloudFront, RDS, DynamoDB, VPC, Elastic Cache, Lambda Working experience with Terraform Experience in creating workflows for Apache Airflow About Roku Roku pioneered streaming to the TV. We connect users to the streaming content they love, enable content publishers to build More ❯

data modeling Proficient in data warehouse technologies (such as Amazon Redshift, Google BigQuery, or Snowflake) Hands-on experience with ETL tools and frameworks, including Apache Airflow, Talend, or dbt Strong programming ability in Python or another data-focused language Knowledgeable about data management best practices, including governance, security More ❯

data modeling Proficient in data warehouse technologies (such as Amazon Redshift, Google BigQuery, or Snowflake) Hands-on experience with ETL tools and frameworks, including Apache Airflow, Talend, or dbt Strong programming ability in Python or another data-focused language Knowledgeable about data management best practices, including governance, security 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 ❯

engagement and performance Techstack: Python (for scripting and data wrangling) SQL (strong experience in querying and transforming data) Experience with building analytics data layers Airflow, dbt (for orchestration and transformation) Cloud data warehouses like BigQuery or Redshift Terraform, Kubernetes (for infrastructure as code and deployment More ❯

engagement and performance Techstack: Python (for scripting and data wrangling) SQL (strong experience in querying and transforming data) Experience with building analytics data layers Airflow, dbt (for orchestration and transformation) Cloud data warehouses like BigQuery or Redshift Terraform, Kubernetes (for infrastructure as code and deployment More ❯

integration of ML solutions into existing workflows. Develop robust, production-quality software artifacts using Python along with large-scale data workflow orchestration platforms (e.g., Airflow). Leverage expertise in cloud computing platforms (AWS and Azure) to build and optimize AI infrastructure, using services like AWS Bedrock, S3, SageMaker, Azure 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 ❯

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 ❯

deployment. Key Responsibilities Design, build and maintain cloud-based data platform infrastructure (AWS, Azure, or GCP) Deploy and manage modern data tools (e.g. DBT, Airflow, Snowflake) Implement Infrastructure as Code using Terraform Automate deployment pipelines using CI/CD tools, preferably Azure Pipelines Ensure platform stability, scalability, and performance … Infrastructure as Code expertise using Terraform CI/CD experience (Azure Pipelines preferred) Docker and Linux tooling Exposure to modern data tools (e.g. DBT, Airflow, Snowflake, Redshift) Agile delivery environment experience More ❯

deployment. Key Responsibilities Design, build and maintain cloud-based data platform infrastructure (AWS, Azure, or GCP) Deploy and manage modern data tools (e.g. DBT, Airflow, Snowflake) Implement Infrastructure as Code using Terraform Automate deployment pipelines using CI/CD tools, preferably Azure Pipelines Ensure platform stability, scalability, and performance … Infrastructure as Code expertise using Terraform CI/CD experience (Azure Pipelines preferred) Docker and Linux tooling Exposure to modern data tools (e.g. DBT, Airflow, Snowflake, Redshift) Agile delivery environment experience More ❯

Engineer will have the following skills and experience: Ability and experience interacting with key stakeholders Strong experience in SQL/Python Good understanding of Airflow/DBT Experience with GCP/AWS Background in CI/CD THE BENEFITS: You will receive a salary, dependent on experience. Salary is More ❯