
Data Engineer – AWS
UBDS
full-time
Posted on:
Location Type: Hybrid
Location: London • United Kingdom
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About the role
- Design, develop, and maintain data pipelines and transformation processes using modern data engineering tools
- Build and manage batch and real-time data processing solutions
- Develop curated, reusable data assets to support downstream analytics and reporting
- Ensure data quality, integrity, and consistency across multiple data sources
- Work with data ingested via APIs, file-based ingestion (e.g. SFTP), and event streams (e.g. Kafka)
- Optimise data pipelines for performance, scalability, and cost efficiency
- Contribute to the development of data platform components and reusable engineering patterns
- Work within established architecture and engineering standards
- Collaborate with DevOps engineers, testers, and architects to deliver end-to-end data solutions
- Support onboarding of new data sources and integration into existing platforms
- Contribute to knowledge sharing and continuous improvement within engineering teams
Requirements
- Experience in data engineering, building and maintaining data pipelines
- Strong hands-on experience with Python and PySpark
- Experience working with AWS data services (e.g. S3, EMR, Glue)
- Experience with event-driven architectures, particularly Kafka
- Understanding of batch and real-time data processing
- Experience working with large-scale datasets and distributed systems
- Familiarity with data quality, validation, and schema management
- Experience using Terraform and GitHub within a DevOps environment
- Ability to work within defined engineering standards and best practices
- Experience with Azure, Databricks, or Microsoft Fabric
- Experience in regulated environments
- Exposure to data migration from legacy systems
- Understanding of analytics, reporting, or data product use cases
- Experience working in collaborative, cross-functional teams
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringdata pipelinesPythonPySparkAWS data servicesKafkaTerraformGitHubAzureDatabricks
Soft Skills
collaborationknowledge sharingcontinuous improvementproblem-solvingcommunicationteamworkadaptabilityattention to detailorganizational skillsability to work within standards