Data Engineer, Quantexa

• Experience designing and building robust, scalable data infrastructure to support high-volume, high-velocity data flows
• Experience in developing and maintaining production-grade ETL and data processing pipelines, with a focus on performance, reliability, and maintainability
• Strong analytical skills, with experience working on real-world, varied datasets to extract insights and improve data quality
• Hands-on experience working with data in cloud-based environments, ideally with distributed systems and modern data platforms
• Familiarity with performance tuning and optimisation techniques for data processing workflows
• A collaborative mindset, with a track record of defining and sharing best practices across teams
• Comfortable working in a fast-paced Agile environment, with a focus on iterative delivery and continuous improvement
• A growth mindset and the drive to thrive within one of the UK’s fastest-growing scale-ups

Desirable

• Applications is an Engineering function within Quantexa’s R&D department that is focused on internally building real-world applications of the Quantexa Platform.
• Data Engineers are focused on building the data infrastructure and processing capabilities that power Quantexa's platform and applications.
• This role encompasses two closely related teams working on the foundational data layer of Quantexa's offerings:
• Data Engineering Accelerators
• Developing Quantexa's libraries for cleansing, parsing and standardising data used in entity resolution
• Finding efficiency/performance improvements through big data testing and building performance tooling
• Owning best practices in entity resolution and network building
• Data Feeds
• Building standardised and reusable code for processing various third party/open source data sets
• Managing an internal data lake for the provision of this data by other teams for testing and analytics
• Owning general best practices for ingesting and processing data to get it ready for use in the Quantexa Platform, including pipelines and scheduling
• The teams work together closely and team members are able to rotate between them to enable knowledge sharing and personal development