Senior BI and Data Analyst

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, technically expert role for someone who builds best-in-class Power BI solutions and is fluent in the full Microsoft data stack. You will be the primary developer of enterprise reporting across commercial, financial, operational, and project performance domains - working directly with business stakeholders to turn complex construction data into trusted, performant analytical outputs.

You will work within a small, high-calibre Digital and Data function, reporting to the Head of BI & Reporting. This is not a management role: it is a senior individual contributor position where technical excellence, speed of delivery, and a deep understanding of construction data are the measures of success.

Roles & responsibilities:

Power BI Development & Data Modelling

• Design, build, and optimise Power BI reports and dashboards from concept through to production deployment, across all business domains.
• Develop complex semantic models with production-quality DAX - including advanced time intelligence, calculation groups, UDFs and performance-optimised measures at scale.
• Write advanced M / Python transformations, including custom functions, parameterised queries, and API connections to source systems.
• Manage model definitions using TMDL under source control (GitHub), following proper branching, review, and release practices.

Data Integration & Pipeline Development

• Build and maintain automated data pipelines (SQL, Power Platform, Azure Data Factory) that replace manual, spreadsheet-heavy reporting workflows.
• Write complex SQL queries, stored procedures, and views to extract and transform data from ERP, commercial, and project control systems.
• Integrate and normalise fragmented data across multiple source systems to deliver a reliable, reconciled analytical layer.
• Configure streaming and real-time datasets for operational reporting that reflects current state, not yesterday’s extract.

Construction Reporting Logic

• Apply working knowledge of construction commercial and operational processes to ensure reports reflect how work is delivered and managed.
• Challenge data that doesn’t align with construction reality and work with source system owners to fix it at the root.

Quality, Governance & Documentation

• Implement automated validation and exception-reporting layers to catch discrepancies before data reaches stakeholders.
• Maintain data dictionaries, lineage documentation, and a technical data catalogue so that metric logic is transparent and not dependent on any single individual.
• Apply row-level security, workspace governance, and enterprise refresh scheduling standards.
• Manage all BI assets through governed deployment pipelines across development, test, and production environments.

Stakeholder Partnership & Self-Service Enablement

• Work directly with finance, commercial, operations, and project teams to understand priorities and translate them into actionable reporting outputs.
• Build reusable, self-service reporting layers that reduce dependency on the central BI function for standard queries.
• Communicate clearly what a report shows, what it doesn’t, and what caveats apply — in language stakeholders understand.

Credentials

• Degree in a quantitative or technical discipline (e.g., Mathematics, Engineering, Data Science, Finance) or equivalent demonstrated practical experience.
• Evidence of continuous learning — recent certifications or a portfolio demonstrating advanced proficiency in Power BI, DAX, TMDL, and at least one of R or Python.

Essential Skills, Knowledge, Experience, Behaviours

Skills & Knowledge

Power BI & DAX

• Expert-level DAX: complex measures, advanced time intelligence, calculation groups, and model performance optimisation (DAX Studio, Tabular Editor)
• Expert-level M / Python: advanced transformations, custom functions, parameterised queries, API connections, custom visuals.
• Strong working knowledge of TMDL for semantic model version control
• Deployment pipelines across dev, test, and production environments
• Streaming and real-time datasets for live operational reporting

SQL & Data Engineering

• Strong SQL: complex queries, stored procedures, views, and CTEs for extraction and transformation.
• Experience building automated data pipelines using SQL, Power Platform, or Azure Data Factory.
• Experience of Power Platform (Apps, Automate, Pages ideally with HTML, CSS, React knowledge) Data reconciliation across enterprise data systems and project control systems with no pre-existing single source of truth.

Source Control

• GitHub (or equivalent): managing BI code, TMDL definitions, and deployment pipelines with branching, review, and release workflows

Statistical Analysis

• R or Python for descriptive and inferential statistics, trend analysis, variance analysis, and data exploration in support of commercial insight

Construction Knowledge

• Working understanding of construction commercial processes: CVRs, cost-to-complete, revenue recognition, margin analysis, subcontractor accounts.
• Familiarity with programme management data: float, critical path, earned value, and how reported progress relates to reality on site.
• Awareness of how construction projects are financially structured: prelims, measured works, variations, provisional sums, retention.

Communication

• Clear, precise communication: able to explain what a report shows, what it doesn’t show, and what caveats apply.
• Comfortable working directly with senior stakeholders across finance, commercial, and operations.

Experience

• Extensive experience of hands-on Power BI development in a complex, multi-system enterprise environment.
• A demonstrable background of data engineering, semantic models, sql query, web scraping, with direct exposure to commercial and operational data.
• Demonstrated track record of replacing manual, spreadsheet-heavy reporting with automated, governed BI solutions.
• Experience reconciling and normalising fragmented data across ERP, commercial, and quality systems.
• Proven ability to work autonomously at pace, managing competing priorities without sacrificing accuracy.

Behaviours

• Technical Rigour: You treat every output with the understanding that a single discrepancy erodes trust in the entire reporting function. Accuracy is non-negotiable.
• Operational Intuition: You interpret data through its real-world context and proactively flag numbers that don’t align with construction reality.
• Root-Cause Orientation: You refuse to paper over data quality issues in the reporting layer. You challenge and fix problems at the source.
• Self-Directed Delivery: You manage your own workload, prioritise effectively, and deliver at pace without needing close supervision.
• Engineering Pragmatism: You know when to provide a rapid tactical answer and when to invest in a properly engineered long-term solution.
• Continuous Improvement: You actively seek better ways to build, automate, and govern reporting — and stay current with the Microsoft data stack.