People Data Engineering Apprentice (Buro Happold Limited)

As a People Data Engineering Apprentice, you’ll play an active role in building and maintaining the systems that help us transform raw data into meaningful insights. Over the course of your Level 5 Data Engineer apprenticeship, you’ll develop your technical and professional skills while working on real projects that make a difference globally. You’ll be supported by experienced colleagues, a structured on-the-job learning plan, and a strong early careers community, helping you develop the technical, professional, and problem solving skills to thrive in data.

What will I be doing?

You’ll be part of the People Data & Solutions team, supporting the end-to-end data lifecycle: ingestion, storage, transformation, and quality - so that analysts, data scientists, and business teams can rely on trusted insights.

Data Engineering & Technical

• Work with people data models to understand how data is structured and used.


• Help design, build, and maintain data pipelines from structured, semi structured, and unstructured sources.


• Support ETL processes: clean, validate, and transform data for downstream use.


• Monitor pipelines, investigate issues, identify root causes, and support fixes.


• Contribute to data quality frameworks (accuracy, completeness, consistency, timeliness).


• Support deployment of new data processes and maintain technical documentation.

Data Governance & Compliance

• Follow data governance, privacy, and security standards.


• Maintain accurate records and audit logs.


• Analyse data flows to identify gaps, risks, or inconsistencies.


• Handle confidential information with professionalism.

Operational & Administrative

• Help prepare routine people data reports and dashboards.


• Respond to data access and data quality queries in a timely manner.


• Assist with small-scale data projects, meeting deadlines with strong attention to detail.


• Support the HR Systems Specialist with data-related system updates and improvements.

Collaboration & Continuous Improvement

• Work closely with analysts, data scientists, HR, and business teams to understand data needs.


• Contribute ideas that improve processes, tools, and documentation.


• Stay curious about data engineering, cloud, and AI—bringing new ideas to the team.