1 to 25 of 31 Apache Airflow Jobs in the Midlands

with multiple languages Technologies: Scala, Java, Python, Spark, Linux and shell scripting, TDD (JUnit), build tools (Maven/Gradle/Ant) Experience in working with process scheduling platforms like Apache Airflow. Open to working in GS proprietary technology like Slang/SECDB An understanding of compute resources and the ability to interpret performance metrics (e.g., CPU, memory, threads, file More ❯

multiple programming languages Technologies: Scala, Java, Python, Spark, Linux and shell scripting, TDD (JUnit), build tools (Maven/Gradle/Ant) Experience in working with process scheduling platforms like Apache Airflow. Open to working in GS proprietary technology like Slang/SECDB An understanding of compute resources and the ability to interpret performance metrics (e.g., CPU, memory, threads, file More ❯

with multiple languages • Technologies: Scala, Java, Python, Spark, Linux and shell scripting, TDD (JUnit), build tools (Maven/Gradle/Ant) • Experience in working with process scheduling platforms like Apache Airflow. • Should be ready to work in GS proprietary technology like Slang/SECDB • An understanding of compute resources and the ability to interpret performance metrics (e.g., CPU, memory More ❯

skills Proficiency in multiple programming languages Technologies: Scala, Java, Python, Spark, Linux, shell scripting, TDD (JUnit), build tools (Maven/Gradle/Ant) Experience with process scheduling platforms like Apache Airflow Willingness to work with proprietary technologies like Slang/SECDB Understanding of compute resources and performance metrics Knowledge of distributed computing frameworks like DASK and cloud processing More ❯

Data Engineer (AI-Driven SaaS Platform) Technologies: Python, Snowflake, Data Modelling, ETL/ELT, Apache Airflow, Kafka, AWS Environment: Large-scale data environment, Fully remote UK, Microservices architecture About the Role Are you a Data Engineering enthusiast who thrives on designing and implementing robust ETL processes, highly scalable data structures, and data pipelines within an enterprise-scale data … infrastructure background, understanding of system migrations, and experience with data warehousing concepts. Technical Skills Deep understanding of SQL and NoSQL databases (MongoDB or similar) Experience with streaming platforms like Apache Kafka Development and maintenance of ELT pipelines Knowledge of data warehousing best practices High proficiency in Apache Kafka and Apache Airflow Strong AWS experience Additional Attributes More ❯

Data Engineer (AI-Driven SaaS plaform) (Python, Snowflake, Data Modelling, ETL/ELT, Apache Airflow, Kafka, AWS) Large-scale data environment Up to £70,000 plus benefits FULLY REMOTE UK Are you a Data Engineering enthusiast who thrives from designing and implementing robust ETL processes, highly scalable data structures and data pipelines within a truly enterprise-scale data … platform integrates Python and Snowflake and you'll need a deep understanding of SQL and NoSQL databases (MongoDB or similar!) You'll also have experience with streaming platforms like Apache Kafka and be able to develop and maintain ELT and essentially bring a solid understanding of data warehousing concepts and best practice. You will understanding Apache Kafka to … a high standard and have solid knowledge of Apache Airflow - from a Cloud perspective, you will be an AWS enthuiast! Naturally you will have good understanding on AWS. I'd love you to be an advocate of Agile too - these guys are massive on Agile Delivery and Scrum - so it's importantly you share a similar mind-set More ❯

and guidance to colleagues at all levels. The ideal candidate must be proficient within an agile delivery environment, and excellent knowledge of DBT & Snowflake, and other technologies including SQL, Airflow, Power BI & Azure Data Factory would be beneficial. The RAC engineering team revolves around a platform mindset, as a Senior Data Engineer, you will extend this culture and ensure … Influence interface with the business and make sense of complicated or incomplete requests What you will need... Great knowledge of technologies including but not limited to: DBT, SQL, Snowflake, Airflow, Azure Data Factory, PowerBI. Be able to work with minimal supervision in a dynamic and timeline sensitive work environment. A strong understanding of agile data development methodologies, values, and More ❯

Senior Data Engineer Hybrid/remote - North-West based £65-80,000 + Bonus + Benefits Are you a data enthusiast eager to work on innovative solutions that impact millions? We're looking for an experienced Senior Data Engineer to More ❯

data platform, ensuring scalability, reliability, and security. Drive modernization by transitioning from legacy systems to a scalable platform. Act as a lead expert for technologies such as AWS, DBT, Airflow, and Databricks. Establish best practices for data modeling, ingestion, storage, streaming, and APIs. Governance & Standards Ensure technical decisions are justified, documented, and aligned with business needs. Lead reviews and … in complex data products. Expertise in data and cloud engineering, including ingestion, transformation, and storage. Hands-on experience with AWS and data services. Advanced skills in SQL, Python, DBT, Airflow, and Redshift. Proficiency in coding, scripting, debugging, testing, and deployment. Ability to mentor others in best practices. Product mindset focused on user needs. Experience designing end-to-end data More ❯

platform, ensuring scalability, reliability, and security. Drive modernisation by transitioning from legacy systems to a lean, scalable platform. Act as a lead expert for technologies such as AWS, DBT, Airflow, and Databricks. Establish best practices for data modelling, ingestion, storage, streaming, and APIs. Governance & Standards Ensure all technical decisions are well-justified, documented, and aligned with business needs. Lead … in data engineering and cloud engineering, including data ingestion, transformation, and storage. Significant hands-on experience with AWS and its data services. Expert-level skills in SQL, Python, DBT, Airflow and Redshift. Confidence in coding, scripting, configuring, versioning, debugging, testing, and deploying. Ability to guide and mentor others in technical best practices. A product mindset, focusing on user needs More ❯

platform, ensuring scalability, reliability, and security. Drive modernisation by transitioning from legacy systems to a lean, scalable platform. Act as a lead expert for technologies such as AWS, DBT, Airflow, and Databricks. Establish best practices for data modelling, ingestion, storage, streaming, and APIs. Governance & Standards Ensure all technical decisions are well-justified, documented, and aligned with business needs. Lead … in data engineering and cloud engineering, including data ingestion, transformation, and storage. Significant hands-on experience with AWS and its data services. Expert-level skills in SQL, Python, DBT, Airflow and Redshift. Confidence in coding, scripting, configuring, versioning, debugging, testing, and deploying. Ability to guide and mentor others in technical best practices. A product mindset, focusing on user needs More ❯

platform, ensuring scalability, reliability, and security. Drive modernisation by transitioning from legacy systems to a lean, scalable platform. Act as a lead expert for technologies such as AWS, DBT, Airflow, and Databricks. Establish best practices for data modelling, ingestion, storage, streaming, and APIs. Governance & Standards Ensure all technical decisions are well-justified, documented, and aligned with business needs. Lead … in data engineering and cloud engineering, including data ingestion, transformation, and storage. Significant hands-on experience with AWS and its data services. Expert-level skills in SQL, Python, DBT, Airflow and Redshift. Confidence in coding, scripting, configuring, versioning, debugging, testing, and deploying. Ability to guide and mentor others in technical best practices. A product mindset, focusing on user needs More ❯

platform, ensuring scalability, reliability, and security. Drive modernisation by transitioning from legacy systems to a lean, scalable platform. Act as a lead expert for technologies such as AWS, DBT, Airflow, and Databricks. Establish best practices for data modelling, ingestion, storage, streaming, and APIs. Governance & Standards Ensure all technical decisions are well-justified, documented, and aligned with business needs. Lead … in data engineering and cloud engineering, including data ingestion, transformation, and storage. Significant hands-on experience with AWS and its data services. Expert-level skills in SQL, Python, DBT, Airflow and Redshift. Confidence in coding, scripting, configuring, versioning, debugging, testing, and deploying. Ability to guide and mentor others in technical best practices. A product mindset, focusing on user needs More ❯

generation systems, Familiarity with MLOps, including Docker, CI/CD, or model deployment in cloud environments, Exposure to cloud platforms (Azure, GCP, AWS) and data tools such as MLflow, Airflow, Databricks, Previous consulting or client-facing experience, Contributions to open-source or technical publications a plus. Being You Diversity is a whole lot more than what we look like More ❯

Utilise Docker for containerisation and Kubernetes for orchestration, ensuring scalable and efficient deployment of applications across both cloud-based and on-premises environments. Workflow Automation: Employ tools such as Apache Airflow to automate data flows and manage complex workflows within hybrid environments. Event Streaming Experience: Utilise event-driven technologies such as Kafka to handle real-time data streams … cloud services. Containerisation and Orchestration Expertise: Solid experience with Docker and Kubernetes in managing applications across both on-premises and cloud platforms. Proficiency in Workflow Automation Tools: Practical experience Apache Airflow in hybrid data environments. Experience in Event Streaming: Proven ability in managing and deploying event streaming platforms like Kafka. Data Security Knowledge: Experience with implementing security practices More ❯

Utilise Docker for containerisation and Kubernetes for orchestration, ensuring scalable and efficient deployment of applications across both cloud-based and on-premises environments. Workflow Automation: Employ tools such as Apache Airflow to automate data flows and manage complex workflows within hybrid environments. Event Streaming Experience: Utilise event-driven technologies such as Kafka to handle real-time data streams … cloud services. Containerisation and Orchestration Expertise: Solid experience with Docker and Kubernetes in managing applications across both on-premises and cloud platforms. Proficiency in Workflow Automation Tools: Practical experience Apache Airflow in hybrid data environments. Experience in Event Streaming: Proven ability in managing and deploying event streaming platforms like Kafka. Data Security Knowledge: Experience with implementing security practices More ❯

Utilise Docker for containerisation and Kubernetes for orchestration, ensuring scalable and efficient deployment of applications across both cloud-based and on-premises environments. Workflow Automation: Employ tools such as Apache Airflow to automate data flows and manage complex workflows within hybrid environments. Event Streaming Experience: Utilise event-driven technologies such as Kafka to handle real-time data streams … cloud services. Containerisation and Orchestration Expertise: Solid experience with Docker and Kubernetes in managing applications across both on-premises and cloud platforms. Proficiency in Workflow Automation Tools: Practical experience Apache Airflow in hybrid data environments. Experience in Event Streaming: Proven ability in managing and deploying event streaming platforms like Kafka. Data Security Knowledge: Experience with implementing security practices More ❯

common life sciences data acquisition software, such as Scientific Data Management Systems (SDMS) or Laboratory Information Management Systems (LIMS). Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow) and data parsing. Familiarity with cloud service models, SaaS infrastructure, and related SDLC. Familiarity with containerization and container orchestration tools (e.g., Docker, Kubernetes). ZONTAL is an More ❯

common life sciences data acquisition software, such as Scientific Data Management Systems (SDMS) or Laboratory Information Management Systems (LIMS). Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow) and data parsing. Familiarity with cloud service models, SaaS infrastructure, and related SDLC. Familiarity with containerization and container orchestration tools (e.g., Docker, Kubernetes). ZONTAL is an More ❯

common life sciences data acquisition software, such as Scientific Data Management Systems (SDMS) or Laboratory Information Management Systems (LIMS). Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow) and data parsing. Familiarity with cloud service models, SaaS infrastructure, and related SDLC. Familiarity with containerization and container orchestration tools (e.g., Docker, Kubernetes). ZONTAL is an More ❯

common life sciences data acquisition software, such as Scientific Data Management Systems (SDMS) or Laboratory Information Management Systems (LIMS). Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow) and data parsing. Familiarity with cloud service models, SaaS infrastructure, and related SDLC. Familiarity with containerization and container orchestration tools (e.g., Docker, Kubernetes). ZONTAL is an More ❯

common life sciences data acquisition software, such as Scientific Data Management Systems (SDMS) or Laboratory Information Management Systems (LIMS). Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow) and data parsing. Familiarity with cloud service models, SaaS infrastructure, and related SDLC. Familiarity with containerization and container orchestration tools (e.g., Docker, Kubernetes). ZONTAL is an More ❯

common life sciences data acquisition software, such as Scientific Data Management Systems (SDMS) or Laboratory Information Management Systems (LIMS). Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow) and data parsing. Familiarity with cloud service models, SaaS infrastructure, and related SDLC. Familiarity with containerization and container orchestration tools (e.g., Docker, Kubernetes). ZONTAL is an More ❯

common life sciences data acquisition software, such as Scientific Data Management Systems (SDMS) or Laboratory Information Management Systems (LIMS). Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow) and data parsing. Familiarity with cloud service models, SaaS infrastructure, and related SDLC. Familiarity with containerization and container orchestration tools (e.g., Docker, Kubernetes). ZONTAL is an More ❯

common life sciences data acquisition software, such as Scientific Data Management Systems (SDMS) or Laboratory Information Management Systems (LIMS). Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow) and data parsing. Familiarity with cloud service models, SaaS infrastructure, and related SDLC. Familiarity with containerization and container orchestration tools (e.g., Docker, Kubernetes). ZONTAL is an More ❯