Business Intelligence and Database Lead

Derby
1 day ago
Create job alert

Job Title: Business Intelligence and Database Lead
Reporting to: Professional Services Director
Purpose of the Role
The Business Intelligence and Database Lead is responsible for developing, maintaining, and enhancing the organisation's data analytics, data quality, and data governance frameworks. The role ensures that business data is accurate, reliable, and aligned with strategic objectives. You will support data‑driven decision‑making by designing insightful dashboards, maintaining data integrity, ensuring compliance with governance standards, and improving data literacy across the organisation.
You will collaborate with global data architecture and modelling teams, regional CAFM support, and operational finance. The role oversees data modelling, reporting architecture, and database governance to support scalable analytics across CAFM systems, BMS telemetry, lifecycle modelling, and operational datasets. This position plays a key role in delivering advanced dashboards and predictive insights for operational teams, asset managers, and clients.
Key Responsibilities

  • Lead and support operational performance reporting across the business and manage a pipeline of reporting requirements (Finance, Operations, P&C, IT, FM).
  • Lead the design and development of enterprise Power BI dashboards and reporting frameworks.
  • Build scalable data models using Power BI, DAX, and Power Query.
  • Lead management of enterprise data platforms including Snowflake, SQL databases, and cloud data warehouses.
  • Design ETL/ELT processes integrating CAFM, IoT, and financial systems.
  • Ensure data integrity, performance optimisation, and security compliance.
  • Implement self‑service BI capabilities for operational and client stakeholders.
  • Maintain a functional specification library for dashboards and ensure design documentation is up to date.
  • Work with the Building Performance Director on predictive and prescriptive analytics, including statistical and machine learning models.
  • Enforce BGIS data governance frameworks and standards, prioritising CAFM systems such as Joblogic and Vantify.
  • Collaborate with CMMS and CAFM Data & Operations Support to automate data quality checks.
  • Implement database migration plans for legacy data domains and ensure appropriate access control and adherence to data retention policies.
  • Document business rules, data definitions, data flows, and schemas.
  • Establish and maintain enterprise data governance frameworks, including data dictionaries, metadata standards, and access control policies.
  • Implement data quality monitoring and validation processes aligned with corporate and client reporting standards.
  • Optimise Power BI datasets for performance and scalability.
  • Deliver training and workshops to提升 data literacy across the business.
  • Support ad‑hoc tasks related to UK service technology operations.
    Additional Responsibilities
  • Oversee data import quality into relevant systems.
  • Work with the Data & BI team on data processes and governance.
    Accountabilities
  • Reports to the Professional Services Director (UK).
  • No direct budget responsibility.
    Key Performance Indicators
  • Enterprise Power BI reporting platform supporting operational and client reporting.
  • Standardised data models across FM systems.
  • Scalable data warehouse architecture.
  • Business‑wide performance analytics dashboards.
  • Strong data governance and security frameworks.
    Person Specification
    Education (Essential)
  • Degree in Data Science, Computer Science, Engineering, or Information Systems.
  • Certifications in Power BI, Microsoft Data Analytics, or Cloud Data Platforms (desirable).
    Education (Desirable)
  • Master's degree in Computer Science, Engineering, IT, or related field.
    Skills & Knowledge (Essential)
  • Advanced Power BI development (DAX, Power Query, data modelling).
  • Strong SQL and relational database knowledge.
  • Experience with cloud platforms (Azure, AWS, GCP) and data lakes.
  • Experience with cloud data platforms such as Snowflake.
  • ETL/ELT pipeline and data integration experience.
  • Understanding of data warehousing architecture.
  • Knowledge of API integrations and data connectors.
    Skills & Knowledge (Desirable)
  • Technical knowledge of SFG20.
  • Experience using Python or R for analytics.
  • Understanding of data governance frameworks (e.g., DAMA‑DMBOK, DCAM).
  • Knowledge of GDPR, ISO 27001 or other data compliance standards.
    Experience (Essential)
  • Minimum 3-5 years' experience in Business Intelligence, data analysis, or data governance.
    Experience (Desirable)
  • Experience with Assets/PPM in a CMMS system.
    Aptitudes
  • Strong analytical and problem‑solving skills.
  • Excellent communication and presentation abilities.
  • High attention to detail and accuracy.
  • Ability to manage multiple priorities and deadlines.
  • Collaborative and able to work effectively across departments.
    Character
  • Enthusiastic and positive approach.
  • Strong customer service focus.
  • Calm and professional under pressure.
  • Reliable, self‑motivated, and able to prioritise effectively.
    Circumstances
  • Flexibility in working patterns is required.
  • Primarily based in BSM offices, with travel to BGIS and client sites across London, the South of England, and occasionally elsewhere.
    #BGISUK

Related Jobs

View all jobs

Business Intelligence and Database Lead

Data Engineer – 11477CM

Data Engineer

Business Intelligence Analyst

Data Analyst Training Course (Excel, SQL & Power BI)

Senior Data Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.