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BuroHappold Engineering

Senior Data Engineer

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Summary

Designs and builds scalable data pipelines and Power BI reporting that power decision-making across Buro Happold's global engineering consultancy, working with lakehouse/medallion architecture on cloud platforms like Microsoft Fabric, Azure, or Databricks while driving data governance and self-service analytics.

Overview

In this role you design and build data platforms that enable smarter decision-making across Buro Happold’s global engineering practice. You’ll fuse modern data engineering with business intelligence, delivering scalable pipelines and insightful reporting while promoting governance and self-service analytics. You join a digital transformation journey that values collaboration, impact, and knowledge sharing across disciplines. This is a chance to shape data-driven decisions on major engineering projects at a respected consultancy.

Pay / Benefits
  • hybrid working
  • competitive salary
  • 25 days holiday + flexible holidays
  • pension scheme
  • flexible benefits (cycle scheme, dental, optical, travel insurance, season ticket loans, corporate discounts)
  • enhanced parenthood leave policies
Responsibilities
  • Design, build, and maintain scalable data pipelines using lakehouse and medallion architecture
  • Integrate data from project systems, engineering tools, databases, and APIs
  • Ensure data quality, governance, lineage, and documentation across the platform
  • Collaborate with IT and platform teams to optimise cloud-based data infrastructure
  • Develop and maintain Power BI dashboards and reporting solutions
  • Own the full reporting lifecycle from requirements to deployment and adoption
  • Implement semantic models, governance, security, and workspace management
  • Support transition from traditional reporting to scalable self-service analytics
  • Contribute to AI-enabled initiatives by integrating data outputs into governed reporting environments
  • Build reusable data assets to support knowledge sharing and organisational learning
  • Support workflow automation by ensuring engineering outputs are captured and accessible
  • Partner with engineers, project managers, and leaders to translate data challenges into solutions
  • Promote a data-driven culture through knowledge sharing, training, and mentoring
  • Support analytics capability growth across the business
Key requirements
  • 3–6 years' experience in Data Engineering, Analytics Engineering, or similar
  • Experience designing and developing modern data pipelines and data models
  • Strong Power BI expertise including data modelling, DAX, dashboards, and workspace management
  • Excellent SQL skills and experience with Python and/or PySpark
  • Experience with cloud data platforms such as Microsoft Fabric, Azure Data Factory, Synapse, Databricks or similar
  • Knowledge of data governance, quality management, and documentation best practices
  • Experience using Git and modern development practices including CI/CD
  • Ability to communicate technical concepts clearly to technical and non-technical audiences
  • communication
  • mentoring
  • collaboration
  • Power BI
  • SQL
  • Python

Skills

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See also

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