Data Engineer / AI Engineer

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
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• 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.

• 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.

• 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.

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