Service Data Analyst (BI Developer)

Rider Levett Bucknall RLB
Manchester
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst, Customer Service — Hybrid

Wastewater Service Delivery Data Analyst

Senior Data Analyst - Customer Services

Data Analyst

Alpha Data Services, Performance Ready Data Analyst, EMEA Lead, Vice President

Alpha Data Services, Performance Ready Data Analyst, EMEA Lead, Vice President

Join to apply for the Service Data Analyst (BI Developer) role at Rider Levett Bucknall RLB


2 weeks ago Be among the first 25 applicants


Department: Sectors and Service


Location: Manchester (Hybrid Working)


Title: Service Data Analyst (BI Developer)


Discipline: Built Asset Consultancy


Location: Any of our UK offices (With Hybrid Working)


Why RLB? At RLB, we live by four simple ideas: Truth, Trust, Together, Tomorrow. Four values that live at the heart of RLB. A place where People Make Progress. We value your skills, talents and unique perspectives – we think they are priceless. Bring them to RLB and you’ll be empowered to shape our future and your career in new and meaningful ways. We’ll give you opportunities to work on some of the most ambitious and exciting projects currently being designed and developed in the built environment sector. You’ll continue to learn and advance as everyone who works for us is provided with a tailored training programme. Our mentoring and reverse mentoring schemes will enable you to share your expertise while gaining fresh insights. What makes RLB unique is our inclusive culture. As an independent, employee-owned business, teamwork and collaboration lies at the heart of everything we do. Hybrid and flexible working arrangements and family-friendly policies are just some of the ways we invest in employee wellbeing. Join us and you will thrive personally as well as professionally.


Role Overview

RLB is seeking a motivated and talented Data Analyst (BI Developer) to join our Built Asset Consultancy team. As a member of the team, you will support a range of technical disciplines – including Building Surveyors, Fire Engineers, Clerk of Works and Designers – to deliver data-driven reporting across a range of projects. Your focus will be on delivering data-driven insights, reporting, and automation using the latest Microsoft technology stack, utilising your skills and understanding of Power BI, Microsoft Fabric, SQL, data services, APIs and Excel to deliver outputs and tools for both internal and external clients.


Role Responsibilities
1. Data Analytics & Visualisation

  • Data Extraction and Manipulation: Extract and load data from multiple sources using SQL, Python, Microsoft Fabric Dataflows, and Pipelines. Apply both ETL and ELT methodologies depending on the use case, ensuring efficient data movement and transformation aligned with the medallion architecture (Bronze, Silver, Gold layers) to support scalable and maintainable analytics solutions.
  • Data Analysis and Visualisation: Analyse structured and semi-structured datasets to uncover patterns, trends, and actionable insights. Develop and maintain visually compelling reports and dashboards using Power BI, SSRS, and Excel. Provide clear documentation for Power BI data models, including data lineage, relationships, and DAX logic.
  • Implementation and Roll-Out: Build, deploy, and maintain a library of templated analytics and reporting solutions for internal and external stakeholders. Support the Service Digital Lead in developing testing protocols, user acceptance criteria, and roll-out plans. Contribute to user training and the design of operating models to ensure successful adoption and ongoing use of digital solutions.

2. Data Integration & Management

  • Assist in developing and optimising data pipelines and user journeys, working with APIs and Microsoft Fabric to ensure seamless data flow.
  • Support the implementation of data governance, quality, and security practices in line with RLB and industry standards.
  • Collaborate with the RLB Data Team to ensure alignment with the wider data architecture and strategy.

3. Collaboration & Stakeholder Engagement

  • Work closely with the internal stakeholders in Service and IT to translate business requirements into actionable data solutions, ensuring consistency and best practice across the organisation.
  • Engage with technical and non-technical stakeholders to understand needs and deliver tailored data products.
  • Provide training and support to end-users, including the adoption of new data and AI tools.
  • Stay up to date with emerging trends in data analytics, Microsoft Fabric, Copilot and other relevant tools.
  • Contribute to the ongoing development of RLB’s digital and data strategy.

Candidate Profile
Qualifications

  • Bachelor’s degree (or equivalent experience and related certifications) in Computer Science, Data Science, Information Systems, or a related field.

Experience
Essential

  • Strong proficiency in Microsoft technologies, especially Power BI, Excel, and Microsoft Fabric (including Data Factory, PySpark, OneLake) as well as DAX and Power Query.
  • Proficiency in SQL, data modelling, and data integration.
  • Familiarity with data analysis, statistical concepts, and data visualisation best practices.

Beneficial

  • Knowledge of Medallion Architecture principles
  • Microsoft Certifications related to Data Platform (DP-300, DP-600, DP-700, PL-300)
  • Transformation of data using Python
  • Knowledge of construction or built environment industry data and classification standards (e.g., COBie, IFC, Uniclass).
  • Experience with API integration and automation.
  • Experience with Copilot or similar AI-powered productivity tools.
  • Exposure to machine learning, predictive analytics, or AI-driven insights.

Behaviours

  • Excellent problem-solving and analytical skills, with a detail-oriented approach.
  • Strong communication skills, both written and verbal, to effectively convey complex ideas to non-technical stakeholders.
  • A passion for data analysis, a curious mindset, and a drive to continuously learn and improve.
  • Collaborative and adaptable, with a focus on delivering value to teams and clients.

RLB Employee Benefits

  • Hybrid Working – Working patterns to support your work-life balance, along with competitive maternity and paternity packages.
  • Well-Rewarded – Competitive salary and generous holiday entitlement, and the opportunity to purchase up to five extra days.
  • Focus On Wellbeing – Health and wellness options, including gym membership and cycle-to-work schemes.
  • Healthcare Packages – Private healthcare insurance and medical support, including dental insurance and eyecare vouchers.
  • Personal Development – Continuous learning and development programme, including established APC and in‑house mentoring schemes.
  • Additional Benefits – Season ticket loan and professional membership subscriptions.
  • Exceptional Exposure – Opportunity to work on diverse projects across different sectors and regions.
  • Social Responsibility – Team and social events, charity fundraising and volunteering activities.

Our Diversity, Equity & Inclusion Promise

We believe in building a diverse and inclusive environment where each person can be themselves, feel valued for their contribution and be challenged and supported to reach their full potential. We have a responsibility to support the communities in which we live and work, and that our workforce should reflect these communities and our clients. Our talent strategy should enable us to overcome bias in the construction industry by recruiting, retaining, developing, and promoting a diverse and inclusive workforce.


If you require any reasonable adjustments to support you during any stage of the application or interview process, please contact our recruitment team at:


#J-18808-Ljbffr

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.

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.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.