Job Description

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 Doing

• Write 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 Bring

• Bachelor'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 Have

• Familiarity 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