Data Engineer - Python, SQL

Data Engineer Manchester (hybrid, 2 days in the office) £This is an opportunity to join a scaling SaaS business where data sits at the heart of the product. You will play a key role in shaping modern data infrastructure that directly supports machine learning systems, real time decision making, and measurable commercial outcomes. The role offers high ownership, greenfield projects, and the chance to influence how data is used across the organisation as it continues to grow. They are a UK based technology scale up building a privacy first, cookieless platform that helps businesses protect and optimise their digital marketing spend. Using machine learning and large scale behavioural data, they analyse vast volumes of traffic in real time to identify low quality or invalid activity. With offices in London and Manchester, they operate at Series A stage with strong funding and a collaborative, engineering led culture. 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. 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 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 Clear scope for progression as the data platform and team continue to scale If you are interested in building high impact data systems in a growing SaaS environment, apply now to find out more about this opportunity.