About this role
Salary: £? - ? per year
Requirements: Deep hands-on expertise in Python, PySpark, and Apache SparkStrong AWS data engineering experience, particularly with AWS GlueStrong Apache Airflow experienceExperience delivering complex data transformation or modernisation programmesStrong software engineering fundamentalsExperience operating at Staff, Principal, or Senior Lead Engineer levelAbility to independently challenge existing thinking and shape technical solutionsGenuine desire to remain hands-on with codeExperience incorporating AI-assisted development tools into engineering workflowsSnowflake experience is beneficial Responsibilities: Provide Staff-level technical leadership across complex data engineering initiativesRemain deeply hands-on with Python, PySpark, and SparkModernise and migrate large-scale data pipelines across AWSDesign and challenge approaches involving AWS Glue, Airflow, and associated technologiesShape scalable data architectures, frameworks, and engineering patternsSupport the development of new data products and reusable capabilitiesChampion AI-assisted development to improve engineering quality and delivery speedRaise engineering standards and capability across multiple teamsHelp shape technical strategy while building and proving solutions in code Technologies: AIAirflowAWSAWS GlueSupportPythonPySparkSnowflakeSparkCloud More:
Were supporting a major UK financial services organisation through a significant data engineering modernisation and transformation programme. This Staff-level contract role involves modernising the organisations data estate, transforming and migrating large-scale pipelines, developing new data products, and adopting modern AI-assisted engineering practices. It is a hybrid position based in London, with three days per week on-site. The initial contract is six months, with a rate of up to £1,300 per day, inside IR35.
last updated 40 week of 2026