51 to 75 of 121 Permanent Apache Airflow Jobs in the UK

and Data Science Closely collaborate with data scientists, product and engineers to innovate and refine the next ML initiatives Good knowledge in Python, SQL, Apache Airflow, Docker, NoSQL Proficiency using tools like Terraform for Infrastructure-as-Code and GCP infrastructure management. Salary Range and Benefits: We are paying more »

how these and other technologies can be applied to business problems to generate value. We currently work in an AWS, Snowflake, Looker, Python and airflow stack; you should be comfortable with these (or similar). The person we’re looking for We are looking for a self-starter who more »

Azure SQL Data Warehouse, or Amazon Redshift Support and learn the associated scheduling logic for data pipelines using scheduling tool such as Autosys or Airflow Read and translate logical data models and use ETL skills to load the physical layer, based on an understanding of timing of data loads more »

existing systems and ingestion pipelines. Requirements: Proven experience working with Python or Java or C# Experience working with ELT/ELT technologies such as Airflow, Argo, Dagster, Spark, Hive Strong technical expertise, especially in data processing and exploration, with a willingness to learn new technologies. A passion for automation more »

in a Data Engineering role Strong SQL and Python development skills Hands-on experience with cloud-based data warehousing technologies (e.g., Snowflake, DBT, FiveTran, AirFlow) Effective communication skills for both technical and non-technical audiences Analytical mindset with attention to detail High energy, enthusiasm, and passion for learning in more »

DBT (Data Build Tool): Strong skills in managing transformations and data pipelines. Python: Expertise in scripting, automation, and data manipulation. Beneficial Experience: Dagster/Airflow: Managing complex workflows. Qlik Sense Cloud/Tableau: Data visualization and reporting. Fivetran/AirByte: Efficient data ingestion. AWS: Familiarity with cloud infrastructure. CI more »

data processing, analysis, and visualization libraries Experienced with SQL and Timeseries databases Skilled in AWS services: S3, EC2, RDS Knowledgeable in ETL tools like Airflow Proficient in Git, CI/CD, testing tools, and documentation best practices Adheres to quality engineering practices including TDD and BDD Nice to have more »

GCP) is highly preferred (experience with other cloud platforms like AWS or Azure is also considered). Familiarity with data pipeline scheduling tools like Apache Airflow. Ability to design, build, and maintain data pipelines for efficient data flow and processing. Understanding of data warehousing best practices and experience in more »

platforms (e.g., AWS Glue, Azure Data Factory, GCP Dataflow). Proficiency in on-premises data integration tools (e.g., Informatica PowerCenter, Datastage, Talend, Pentaho, Nifi, Airflow). General knowledge of relational databases (e.g., SQL Server, Oracle, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra, Couchbase). Experience with data warehousing solutions more »

web scraping and other data ingestion methods and tools. Knowledge of distributed computing frameworks (Hadoop, Spark, Hive, Presto). Experience with data orchestration tools (Airflow, Orchestra, Azkaban). Expertise in cloud data warehousing and core data modelling concepts. Proficiency in version control systems (Git) and experience with CI/ more »

Mathematics, Finance, Accounting, Economics or a related field or equivalent work experience (3+ years) Experience in: Some knowledge of database orchestration technologies + ETL (Airflow, DBT, Databricks) Working understanding of financial concepts and systems Ability to recognize and diagnose potential errors or data inconsistencies between multiple reports Working knowledge more »

Proven experience in MLOps and deploying machine learning models on Kubernetes. Proficiency in cloud technologies, AWS, GCP, Azure Experience with data orchestration tools (e.g., Apache Airflow). Familiarity with Terraform for CI/CD and infrastructure as code. Strong programming skills in software development. A cloud-agnostic mindset more »

testing, and maintenance of data pipelines and data storage systems on Google Cloud Platform (GCP). You will be working with technologies such as Apache Airflow, BigQuery, Python, and SQL to transform and load large data sets, ensuring high data quality and accessibility for business intelligence and analytics more »

and IAM. Experience with containerization and orchestration tools, particularly Kubernetes. Proficiency in infrastructure as code tools such as Terraform, Ansible, or CloudFormation. Experience in Apache Airflow, AWS Backup & S3 versioning Solid understanding of CI/CD concepts and experience implementing CI/CD pipelines using tools like Jenkins more »

load data to Snowflake. Converting SAS based module to python based Candidates who have data management experience in Snowflake with expertise in Python, DBT, Airflow or similar technologies Must have hands on experience in DBT & SQL Snowflake (added advantage more »

hands on and will require exposure to some essential tools and a high level of financial knowledge. Good exposure to AWS technologies is essential, Airflow would be desirable. Experience with batch processing is required. Experience working with a Linux environment. Scripting exposure within either Python, Bash or Shell scripting. more »

successful Lead Data Engineer will have: Experience leading a Data Engineering team. Extensive working experience with GCP, SQL and DBT. Proficient in: Kafka, Dataform, Airflow, Tableau, PowerBI, Redshift, Snowflake, Terraform and BigQuery. What's in it for the successful Lead Data Engineer: Hybrid working for a better work/ more »

as thinking strategically and proactively identifying opportunities. You have experience collaborating with senior business stakeholders and finance teams. You have working knowledge of Python, Airflow, dbt, Bigquery, and Looker. Additional desirables: Experience in one or more finance domains, such as Financial Reporting, Treasury, Regulatory Reporting, Financial Planning & Analysis, Financial more »

an autonomous environment. 5+ years SQL experience developing data pipelines in a cloud based database environment (e.g.BigQuery), including scheduling your own queries (e.g. using Airflow or Stitch) 3+ years experience delivering data products in a modern BI technology (ideally Looker) or open source data frameworks Experience managing end-to more »

Looking for: -Data Engineering + Data Science Experience -Strong ETL Experience -Experience with Computer Vision -Experience in Remote Sensing highly desirable Stack: Python, PyTorch, AirFlow, PySpark (equivalent tools are fine more »

working on very complex systems Strong experience with Computer vision Longevity in their previous roles Experience with Remote Sensing highly desirable Stack: Python, PyTorch, AirFlow, PySpark (equivalent tools are fine more »

a leading commodities trading firm. Outside of IR35 Hybrid working - 2/3 days in London office Experience Required: - Commodities industry experience Weather forecasting Airflow (or equivalent data orchestration platforms) Data Modeling (Star Schema) Data Warehousing Data Pipeline Orchestration (Kafka) On-Prem SQL more »

Experienced creating data pipelines on a cloud (preferably AWS) environment CI/CD experience Containerization experience (Docker, Kubernetes, etc.) Experience with SQS/SNS, Apache Kafka, RabbitMQ Other interesting/bonus skills – Airflow, Trino, Apache Iceburg, Postgres, MongoDB You *must* be eligible to work in your chosen more »

and maintain scalable data architectures, including pipelines and cloud-based data warehouses. Tech: Python (NumPy, Pandas), SQL, ETL, Cloud (AWS, Azure or GCP), Snowflake, Airflow, BigQuery, PowerBI/Tableau Industry: Fintech, Maritime trading Immersum are supporting the growth of a specialist consultancy who solely specialise in the Maritime trading … developing and optimising ETL pipelines. Version Control: Experience with Git for code collaboration and change tracking. Data Pipeline Tools: Proficiency with tools such as Apache Airflow. Cloud Platforms: Familiarity with AWS, Azure, Snowflake, and GCP. Visualisation: Tableau or PowerBI Delivery Tools: Familiarity with agile backlogs, code repositories, automated builds more »

a production setting. Knowledge of developing real-time data stream systems (ideally Kafka). Proven track record in developing data systems using PySpark and Apache Spark for batch processing. Capable of managing data intake from various sources, including data streams, unstructured data, relational databases, and NoSQL databases. Extensive knowledge … data pipelines. Proficiency in Python programming (knowledge of Scala or Rust is a plus). Familiarity with ETL principles in contemporary data applications (Dagster, Airflow, Perfect). Familiarity with AWS services such as Glue, Redshift, Athena, and S3. Proficiency with Terraform, Kubernetes, and ArgoCD (expertise not required; cloud team more »