Posted: 9 June
The role
As a Data Engineer / AI Engineer in the Operational Analytics team, you will be the hands-on builder who designs, develops, and maintains our data infrastructure from the ground up — ahead of full IT handover. This is not a Database Administrator role. We need someone who has built things from scratch, is comfortable operating in ambiguity, and is excited to shape both the engineering and AI layer of a growing analytics function.What You'll Be DoingWrite clean, well-documented Python and SQL code with a focus on performance, maintainability, and reusability.Architect and develop data models within our centralized data platform, ensuring data quality, consistency, and traceability.Build new data assets from raw sources, bridging operational systems and the analytical layer until IT takes full ownership.Develop and implement AI/ML-enabled data features — including data enrichment, anomaly detection, and predictive pipelines.Integrate AI APIs and LLM-based tools into data workflows to accelerate analytics at scale.Work closely with analysts and business stakeholders to understand data needs and translate them into robust engineering solutions.Design, build, and maintain scalable ETL/ELT pipelines that ingest, transform, and serve data across the organization.Support the transition of built solutions to IT once production-ready, ensuring proper documentation and handover.What You'll BringBachelor's or Master's degree in Computer Science, Data Science, Engineering or a related field.3+ years of hands-on experience in data engineering, strong managing large datasets and fluent with SQL querying, including building ETL/ELT pipelines and data models from scratch.Strong proficiency in Python (pandas, PySpark, or similar) and SQL.Experience with cloud-based data platforms (e.g., Snowflake, Azure DL, AWS S3, Databricks).Practical knowledge of AI/ML concepts and experience integrating AI capabilities into data products or pipelines.Excellent communication skills: able to engage with business stakeholders and translate requirements into technical designs.Comfortable working as a builder and owner before IT infrastructure is fully in place — a 'zero-to-one' mindset.Nice to HaveFamiliarity with orchestration tools such as Apache Airflow, dbt, or Azure Data Factory.Exposure to LLM frameworks (LangChain, OpenAI API, Azure OpenAI).Experience with version control (Git/GitHub) and CI/CD practices for data pipelines.BracknellBracknell ForestUnited Kingdom
#J-18808-Ljbffr
