17 of 17 Permanent Apache Airflow Jobs in Edinburgh

Senior Data Engineer/Data Analytics Engineer - Full Remote Working from anywhere in the UK SQL+Python+ETL+ Apache Airflow Our client is a global leading and fast growing high tech company: -Over 6,500 employees across 20+ offices; -300 Million+ active users on some of the platforms they developed … ensure data quality, and support business decision-making with high-quality datasets. -Work across technology stack: SQL, Python, ETL, Big Query, Spark, Hadoop, Git, Apache Airflow, Data Architecture, Data Warehousing -Design and develop scalable ETL pipelines to automate data processes and optimize delivery -Implement and manage data warehousing … solutions, ensuring data integrity through rigorous testing and validation -Lead, plan and execute workflow migration and data orchestration using Apache Airflow -Focus on data engineering and data analytics Requirements: -5+ years of experience in SQL -5+ years of development in Python -MUST have strong experience in More ❯

early and providing strategic guidance. Support the ongoing development of integration strategies involving Managed File Transfer solutions (e.g., GoAnywhere) and data orchestration platforms (e.g., Apache Airflow). Provide hands-on support and detailed guidance on particularly complex integration designs where necessary. Maintain current knowledge of industry trends, technology … and migrations. Familiarity with IBM Maximo asset management platform. Knowledge and experience with Managed File Transfer solutions (e.g., GoAnywhere). Understanding and experience with Apache Airflow orchestration platform. Strong grasp of integration best practices, security considerations, and data flow management. Ability to work collaboratively across distributed teams and More ❯

processes. Technical Skills Programming: Proficiency in Python, Java, Scala, or similar languages. Big Data Technologies: Hands-on experience with big data tools e.g. (Databricks, Apache Spark, Hadoop). Cloud Platforms: Familiarity with AWS, Azure, GCP, or other cloud ecosystems for data engineering tasks. Expertise in relational databases (e.g. postgres … sql server) Data Integration Tools: Knowledge of platforms like Airflow, Apache NiFi, or Talend. Data Storage and Modelling: Experience with data warehousing tools (e.g. Snowflake, Redshift, BigQuery) and schema design. Version Control and CI/CD: Familiarity with Git, Docker, and CI/CD pipelines for deployment. Experience More ❯

with tools and packages like Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks. Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. Proficiency in data pre-processing, data wrangling, and augmentation techniques. Experience with cloud platforms (e.g. AWS, Google Cloud, or Azure) for deploying scalable More ❯

processes. Technical Skills Programming: Proficiency in Python, Java, Scala, or similar languages. Big Data Technologies: Hands-on experience with big data tools e.g. (Databricks, Apache Spark, Hadoop). Cloud Platforms: Familiarity with AWS, Azure, GCP, or other cloud ecosystems for data engineering tasks. Expertise in relational databases (e.g. postgres … sql server) Data Integration Tools: Knowledge of platforms like Airflow, Apache NiFi, or Talend. Data Storage and Modelling: Experience with data warehousing tools (e.g. Snowflake, Redshift, BigQuery) and schema design. Version Control and CI/CD: Familiarity with Git, Docker, and CI/CD pipelines for deployment. Experience More ❯

related field, with a focus on building scalable data systems and platforms. Strong expertise with modern data tools and frameworks such as Spark , dbt , Airflow , Kafka , Databricks , and cloud-native services (AWS, GCP, or Azure). Deep understanding of data modeling , distributed systems , streaming architectures , and ETL/ELT More ❯

love to talk to you if: You’ve got solid experience working with Python, SQL, Spar and data pipeline tools such as dbt or Airflow You’re comfortable working across cloud platforms – especially AWS (Glue, Lambda, Athena), Azure (Data Factory, Synapse), or GCP (Dataflow, BigQuery, Cloud Composer) You have More ❯

a related field, with a focus on building scalable data systems and platforms. Expertise in modern data tools and frameworks such as Spark, dbt, Airflow, Kafka, Databricks, and cloud-native services (AWS, GCP, or Azure) Understanding of data modeling, distributed systems, ETL/ELT pipelines, and streaming architectures Proficiency More ❯

related field, with a focus on building scalable data systems and platforms. Strong expertise in modern data tools and frameworks such as Spark, dbt, Airflow, Kafka, Databricks, and cloud-native services (AWS, GCP, or Azure) Deep understanding of data modeling, distributed systems, ETL/ELT pipelines, and streaming architectures More ❯

related field, with a focus on building scalable data systems and platforms. Strong expertise with modern data tools and frameworks such as Spark , dbt , Airflow , Kafka , Databricks , and cloud-native services (AWS, GCP, or Azure). Deep understanding of data modeling , distributed systems , streaming architectures , and ETL/ELT More ❯

You've led technical delivery of data engineering projects in a consultancy or client-facing environment You're experienced with Python, SQL, .NET, dbt, Airflow and cloud-native data tools (AWS, GCP or Azure) You have strong knowledge of data architecture patterns - including Lakehouse and modern warehouse design (e.g. More ❯

DevOps automation, idempotent deployment testing, and continuous delivery pipelines Networking and security protocols, load balancers, API Gateways ETL tooling and workflow engines (e.g., Spark, Airflow, Dagster, Flyte) Accelerated compute libraries and hardware (e.g. pytorch, NVIDIA GPUs) Data modeling, and strategies for cleaning and validating data at scale Performance tuning More ❯

general analytics use case. Additionally, having experience with Kubernetes or other platforms for containerized applications as well as working with orchestration systems such as Apache Airflow would be essential to succeed in this role. The ideal candidate for this role would need to have proficiency in programming languages More ❯

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 More ❯

access to users throughout Trustpilot Design, build, maintain, and rigorously monitor robust data pipelines and transformative models using our modern data stack, including GCP, Airflow, dbt, and potentially emerging technologies like real-time streaming platforms Develop and manage reverse ETL processes to seamlessly integrate data with our commercial systems More ❯

the infrastructure provisioning • Set up infrastructure security • Implementation of IAM policy and permissions for applications and GitHub • Changes of environment variables for applications and Airflow DAGS If you are interested please hit apply with your updated CV and we will arrange a call to further your application. More ❯

including data pipelines, orchestration and modelling. Lead the team in building and maintaining robust data pipelines, data models, and infrastructure using tools such as Airflow, AWS Redshift, DBT and Looker.Ensuring the team follows agile methodologies to improve delivery cadence and responsiveness. Contribute to hands-on coding, particularly in areas … foster team growth and development Strong understanding of the data engineering lifecycle, from ingestion to consumption Hands-on experience with our data stack (Redshift, Airflow, Python, DVT, MongoDB, AWS, Looker, Docker) Understanding of data modelling, transformation, and orchestration best practices Experience delivering both internal analytics platforms and external data More ❯