Bovis builds enduring partnerships, bringing together the right expertise, the right capabilities and the right resources to deliver the most complex projects.
We know from decades of experience that successful delivery of multi-year complex projects requires close working relationships and collaboration through the supply chain. That’s why we share risk and invest in people and relationships at every level.
We make things happen, anticipating challenges before they arise. Drawing on our highly experienced, multi-disciplinary teams, we bring a fresh perspective, tailoring our approach to the specific demands of the project, helping to simplify complexity and minimise risk.
What we are recruiting for:
This is a hands-on development role for someone early in their data career who wants to build real technical depth in Power BI, SQL, and the Microsoft data stack — inside a business where data directly drives operational and commercial decisions.
You will work within a small, high-calibre Digital and Data function, supporting the Senior BI & Data Analyst and Head of BI & Reporting in delivering enterprise reporting across the organisation. You will build reports, maintain data pipelines, improve data quality, and increasingly own reporting outputs end-to-end as your capability grows.
This is not an admin or data-entry role. You will be writing DAX, SQL, and M from day one. You will be expected to learn fast, take ownership of your outputs, and develop a genuine understanding of how construction businesses generate, manage, and report on data.
Roles & responsibilities:
Report Development & Maintenance
- Build and maintain Power BI reports and dashboards under the direction of the Senior BI & Data Analyst, following established development standards and design patterns.
- Write DAX measures, calculated columns, and M / Power Query transformations to meet defined reporting requirements.
- Maintain and extend existing semantic models, ensuring changes are tested, documented, and deployed through governed pipelines.
- Troubleshoot report performance issues, applying optimisation techniques with guidance from senior team members.
Data Preparation & Quality
- Write SQL queries to extract, transform, and validate data from ERP, commercial, and project control source systems.
- Identify and investigate data quality issues — missing records, broken joins, unexpected nulls, reconciliation failures — and escalate or resolve them at source.
- Support the build and maintenance of automated data pipelines that replace manual data handling.
- Maintain data dictionaries, lineage records, and technical documentation so that metric definitions are clear and auditable.
Business Support & Stakeholder Interaction
- Respond to reporting requests from finance, commercial, operations, and project teams, ensuring outputs are accurate and delivered to agreed timelines.
- Learn how construction commercial and operational processes create the data you are reporting on — CVRs, cost forecasts, programme status, subcontractor accounts — so that you can spot anomalies and ask the right questions.
- Communicate clearly with non-technical stakeholders about what reports show, what they don’t, and where caveats apply.
Governance & Standards
- Follow source control practices using GitHub: committing code, managing branches, and participating in code reviews.
- Adhere to workspace governance, row-level security configurations, and deployment pipeline standards set by the team.
- Apply naming conventions, folder structures, and documentation standards consistently across all BI assets.
Continuous Development
- Actively develop your technical skills across Power BI, DAX, SQL, Python/R, and the broader Microsoft data stack.
- Seek feedback, learn from code reviews, and progressively take on more complex and autonomous work.
- Develop your understanding of construction industry data, commercial processes, and reporting requirements through on-the-job exposure and structured learning.
Credentials
- Degree in a quantitative or technical discipline (e.g., Mathematics, Computer Science, Engineering, Data Science, Finance, Economics) or equivalent practical experience with a strong portfolio
Essential Skills, Knowledge, Experience, Behaviours
Skills & Knowledge
Power BI & DAX
- Working knowledge of Power BI Desktop: report design, data modelling, relationships, and basic DAX measures.
- Ability to write and troubleshoot M / Power Query transformations for data shaping and cleansing Understanding of star schema design principles and why model structure matters for performance.
SQL
- Competent SQL: SELECT, JOIN, WHERE, GROUP BY, subqueries, and CTEs for data extraction and validation.
- Ability to read and understand stored procedures and views written by others.
Source Control
- Basic familiarity with Git concepts: commits, branches, pull requests, and merge workflows.
Data Quality
- A methodical approach to data validation: checking row counts, reconciling totals, identifying nulls and duplicates.
- Willingness to investigate and resolve data issues rather than work around them.
Communication
- Clear written and verbal communication: able to document work, explain findings, and ask precise questions.
- Comfortable working in a team and interacting with stakeholders outside the immediate data function.
Experience
- Demonstratable experience working with data in a professional setting — this could be in a dedicated analyst role, a graduate programme, or a data-adjacent role where you were hands-on with BI tools and SQL.
- Demonstrated ability to build Power BI reports that are used by others in a business context (not just personal projects or coursework).
- Experience writing SQL against relational databases in a work or structured project environment.
- Evidence of self-directed learning: completing certifications, building a portfolio, contributing to data projects, or similar.
Behaviours
- Accuracy First: You check your work. You reconcile your numbers. You don’t assume the data is right — you verify it.
- Curiosity: You want to understand why the data looks the way it does, not just what it says. You ask questions and dig into the context behind the numbers.
- Ownership: You take responsibility for your outputs. When something isn’t right, you flag it and fix it rather than hoping nobody notices.
- Self-Directed Learning: You don’t wait to be taught. You actively pursue technical development through courses, practice, experimentation, and peer learning.
- Pragmatism: You understand that delivery matters. You can balance doing things properly with getting things done on time.
- Team Orientation: You work openly, share your progress, ask for help when you need it, and contribute to a culture of high standards and mutual support.
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