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# AWS Data Engineer

- **Company:** Harnham
- **Location:** Manchester, UK
- **Salary:** £70,000.0 - £90,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Amazon Web Services, Amazon S3, Data as a Services, Data Infrastructure, Data Systems, Data Warehousing, Python (Programming Language), Standard Sql, Data Streaming, Systems Integration, Data Ingestion, AWS Data Analytics, Tools for Reporting, Video Streaming, Data Pipelines, Amazon Redshift
- **Published:** May 17, 2026
- **Apply:** https://find.jobs/jobs-near-me/aws-data-engineer-manchester/2773460507-2/

## About the Role

* Strong commercial experience building production grade data pipelines using Python and SQL
 * Hands on experience with AWS data services such as S3, Redshift, Glue, Athena, and streaming technologies like Kinesis
 * Experience working with large scale, high velocity event data and understanding the trade offs around cost, performance, and reliability
 * Ability to think beyond implementation and understand how data supports business and product outcomes
 * Comfortable collaborating across Data, Engineering, and Product in a fast moving environment
 * Exposure to ML or analytics use cases, including preparing data for modelling or experimentation, is highly beneficial

## Description

You will sit within the Data and Platform function, working closely with Data Science, Engineering, and Product teams to design and run reliable, scalable data systems. Key responsibilities include:

 * Designing and owning batch and streaming data ingestion pipelines on AWS
 * Building and maintaining ML ready datasets to support model training, inference, and experimentation
 * Improving data warehouse design and performance within AWS Redshift, including refactoring poorly structured data
 * Integrating new and underused data sources to unlock additional value
 * Supporting feature store development and data pipelines for A/B testing and analytics tools
 * Optimising data systems for cost, performance, reliability, and data freshness
 * Contributing to greenfield initiatives while scaling existing data infrastructure handling very high volumes of event data


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