12 of 12 Permanent Apache Airflow Jobs in the City of London

data cataloging and metadata management using tools like AWS Glue Data Catalog. Demonstrated self-sufficiency in exploring new tools, troubleshooting issues, and continuously improving processes. Hands-on experience with Apache Airflow for orchestrating complex data workflows and ensuring reliable execution. Understanding of cloud security and governance practices including IAM, KMS, and data access policies. Experience with monitoring and More ❯

data cataloging and metadata management using tools like AWS Glue Data Catalog. Demonstrated self-sufficiency in exploring new tools, troubleshooting issues, and continuously improving processes. Hands-on experience with Apache Airflow for orchestrating complex data workflows and ensuring reliable execution. Understanding of cloud security and governance practices including IAM, KMS, and data access policies. Experience with monitoring and More ❯

in data leadership – ideally within fintech, SaaS, or regulated tech environments. Technical depth across data engineering, analytics, or data science. Hands-on familiarity with modern data stacks – SQL, dbt, Airflow, Snowflake, Looker/Power BI. Understanding of the AI/ML lifecycle – including tooling (Python, MLflow) and best-practice MLOps. Comfortable working across finance, risk, and commercial functions. Experience More ❯

b2c who you will have heard of/used, who are seeking 2x Data Engineers to join them asap on an initial 6 months contract. Python, SQL, AWS, dbt, Airflow (spark/scala a bonus) 6 months Outside IR35 (ltd company) £500-600 per day Asap start More ❯

network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience More ❯

network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience More ❯

optimisation. This is an ideal role for someone looking to hit the ground running, work on complex challenges with autonomy. Role Requirements: Exceptional ability with tools such as Python, Airflow, SQL, and at least one Cloud provider Experience forecasting, customer, and propensity models Experience with building machine learning models and deploying at scale 2:1 or above in Mathematics More ❯

optimisation. This is an ideal role for someone looking to hit the ground running, work on complex challenges with autonomy. Role Requirements: Exceptional ability with tools such as Python, Airflow, SQL, and at least one Cloud provider Experience forecasting, customer, and propensity models Experience with building machine learning models and deploying at scale 2:1 or above in Mathematics More ❯

analytics, and software development, contributing to innovative products and services that drive real business value. Key Responsibilities Design and implement robust data pipelines using tools such as dbt and Airflow . Collaborate with clients to understand business challenges and deliver tailored data solutions. Transform raw data into structured, actionable datasets for use in AI , predictive modelling , and platform development … the ability to engage stakeholders and translate technical work into business outcomes. Hands-on experience with cloud platforms (preferably AWS or Snowflake) and ETL/ELT orchestration tools (e.g. Airflow, dbt). Desirable Skills Familiarity with tools such as MongoDB , Glue , Athena , and React . Experience in API development and working with modern data infrastructure. Ability to work independently More ❯

colleagues. Nice to Have Skills Experience working with GCP (BigQuery) or other modern cloud-native data warehouses (e.g. Snowflake, Redshift). Familiarity with data pipelining and orchestration systems (e.g. Airflow). Understanding of modern analytics architectures and data visualisation tools (we use Preset.io/Apache Superset). Exposure to CI/CD pipelines (GitLab CI preferred). Experience More ❯

colleagues. Nice to Have Skills Experience working with GCP (BigQuery) or other modern cloud-native data warehouses (e.g. Snowflake, Redshift). Familiarity with data pipelining and orchestration systems (e.g. Airflow). Understanding of modern analytics architectures and data visualisation tools (we use Preset.io/Apache Superset). Exposure to CI/CD pipelines (GitLab CI preferred). Experience More ❯

Collaborate with ML researchers and biologists to translate raw data into actionable insights and high-quality training data Scale distributed systems using Kubernetes, Terraform, and orchestration tools such as Airflow, Flyte, or Temporal Write clean, extensible, and well-tested code to ensure long-term maintainability and collaboration across teams About You We are looking for data and platform engineers … Experience designing and implementing large-scale data storage systems (feature stores, timeseries databases, warehouses, or object stores) Strong distributed systems and infrastructure skills (Kubernetes, Terraform, orchestration frameworks such as Airflow/Flyte/Temporal) Hands-on cloud engineering experience (AWS, GCP, or Azure) Strong software engineering fundamentals, with a track record of writing maintainable, testable, and extensible code Familiarity More ❯