1 to 25 of 48 Apache Airflow Jobs in the North West

Databrew. They are experienced in developing batch and real-time data pipelines for Data Warehouse and Datalake, utilizing AWS Kinesis and Managed Streaming for Apache Kafka. They are also proficient in using open source technologies like Apache Airflow and dbt, Spark/Python or Spark/Scala More ❯

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 ❯

working with data formats such as JSON, CSV, and Parquet. • Strong understanding of IT concepts, including security, IAM, Key Vault, and networking. • Exposure to Apache Airflow and DBT is a bonus. • Familiarity with agile principles and practices. • Experience with Azure DevOps pipelines. The "Nice to Haves": • Certification in More ❯

help you get there: Understanding of cloud computing security concepts Proficiency with IaC tools like Terraform or CloudFormation. Experience with workflow orchestration tools (e.g., Airflow, Dagster). Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in Agile environments with More ❯

help you get there: Understanding of cloud computing security concepts Proficiency with IaC tools like Terraform or CloudFormation. Experience with workflow orchestration tools (e.g., Airflow, Dagster). Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in Agile environments with More ❯

help you get there: Understanding of cloud computing security concepts Proficiency with IaC tools like Terraform or CloudFormation. Experience with workflow orchestration tools (e.g., Airflow, Dagster). Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in Agile environments with More ❯

with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as More ❯

with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as More ❯

with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as 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 ❯

and support automated monitoring systems to detect data anomalies, system failures, and performance issues and leverage advanced scripting and orchestration tools (e.g., Python, Bash, Apache Airflow) to automate workflows and reduce operational overhead. Root Cause Analysis & Incident Management: Lead post-incident reviews, perform root cause analysis for data More ❯

and support automated monitoring systems to detect data anomalies, system failures, and performance issues and leverage advanced scripting and orchestration tools (e.g., Python, Bash, Apache Airflow) to automate workflows and reduce operational overhead. Root Cause Analysis & Incident Management: Lead post-incident reviews, perform root cause analysis for data 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 Python and at least one other programming language such as Java, or Scala Willingness to mentor more junior members of More ❯

operational targets crossing multiple departments Nice-to-have experience: Infrastructure as code (Terraform, cloud formation etc...) Cloud platforms (Aws, Azure, GCP etc..) Data orchestration (Airflow, Dagster etc...) The Team The Data & Analytics department serves as the central hub for data engineering and insights across our organization, comprising four essential More ❯

processes Hands-on experience with cloud platforms (GCP, AWS, Azure) and their data-specific services Proficiency in Python, SQL, and data orchestration tools (e.g., Airflow, DBT) Experience with modern data warehouse technologies (BigQuery, Snowflake, Redshift, etc.) Strong understanding of data modeling, data governance, and data quality principles Excellent communication More ❯

following: A track record of consolidating data sources, creating pipelines, and ideally a software engineering mindset. Excellent experience with Containers. Strong knowledge of Python, Airflow, SQL, and Linux. Proficient in AWS Lambda, ECS, Athena, S3, Kinesis, Glue, CloudWatch/Terraform/CDK, Tableau Online. They are particularly keen on More ❯

series forecasting, and model evaluation Familiarity with cloud platforms (AWS and/or GCP) Experience with productionising models using tools like Kubernetes, Docker, and Airflow Good knowledge of NLP techniques for text analysis Ability to design and run effective experiments (A/B, multivariate) Excellent communicator – able to explain More ❯

develop and deploy Feature Engineering and Modeling applications to data platforms built on Databricks or similar platforms and platform components (e.g., Snowflake, ML Flow, Airflow, etc.). Demonstrated experience in using Azure-based cloud applications, services and infrastructure or significant, transferrable experience with other Cloud Providers (e.g., AWS or 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 fields. Benefits: Competitive salary and performance bonuses Flexible working options More ❯

Dataplex, Dataflow, Cloud Functions, Cloud Run, Pub/Sub, GCS, Vertex AI, GKE) or similar cloud platforms Familiarity with open-source data-stack tools (Airflow, DBT, Kafka, Great Expectation, etc.) Appreciation of modern cloud data stack, headless BI, analytics engineering, Data Mesh, and Lake House Although not essential, it More ❯

to provide the necessary infrastructure, resources, and interfaces for data loading and LLM workflows. Use Python and large-scale data workflow orchestration platforms (e.g. Airflow) to build software artifacts for ETL, integrating diverse data formats and storage technologies, and incorporate them into robust data workflows and dynamic systems Design More ❯

Data Scientists use (we don't expect applicants to have experience with all of these): Python and Databricks for Data Science, Spark, MLFlow and Airflow for ML Workflows, Google Cloud Platform for our analytics infrastructure, dbt and BigQuery for data modelling and warehousing. We are looking to grow our More ❯

/testing best practices. - Experience of hiring and growing a diverse team. DESIRED BUT NOT REQUIRED: - Experience with Next.JS - Experience with technologies such as Airflow, EMR, Redis, Postgres - Experience of working within a Data Platform team. - Experience of analytics, tracking or experimentation. If you can bring some of these More ❯

platform supports industry-leading Data Science tools. While experience with all these technologies is not expected, familiarity is beneficial: Python and Databricks Spark, MLFlow, Airflow Google Cloud Platform dbt and BigQuery Examples of our data science work can be found on our engineering blog . What We’re Looking More ❯

Technologies That Our Data Scientists Use (we Don’t Expect You To Have Experience With All Of These) Python and Databricks Spark, MLFlow, and Airflow for ML Workflows Google Cloud Platform for our analytics infrastructure dbt and BigQuery for data modelling and warehousing Some examples of our data science More ❯