We’re looking for a Data Engineer to help build and scale the data foundations that power modern AI and generative AI solutions. This role is focused on designing resilient data pipelines that support advanced analytics, ML, and LLM-driven use cases across a range of data types.
The role:
You’ll work closely with AI, ML, and platform teams to shape how data is collected, processed, and made available for downstream intelligence. The focus is on robust engineering, clean data, and systems that can scale as AI use cases move into production.
What you’ll be doing:
* Building and maintaining Python-based data pipelines that handle ingestion, transformation, and enrichment of both structured and unstructured data
* Applying AI-assisted techniques to data preparation, including classification, extraction, and feature creation to support ML and LLM workflows
* Connecting data pipelines into Azure-based platforms, including data lakes and cloud-native services
* Ensuring pipelines are reliable and performant through testing, monitoring, and continuous optimisation
* Partnering with data scientists, AI engineers, and platform teams to support end-to-end AI delivery
What we’re looking for:
* Solid hands‑on experience as a data engineer, with Python as a core language
* Proven experience delivering data pipelines in production environments at scale
* Exposure to AI, ML, or generative AI use cases within data platforms
* Practical experience working with Azure Data Lake and related Azure data services
* A strong engineering mindset with attention to data quality, system reliability, and performance
* Comfortable operating in collaborative, cross‑functional teams
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