Senior Business Intelligence Developer

Sellick Partnership
Preston
1 month ago
Applications closed

Related Jobs

View all jobs

Business Intelligence Developer / Reporting Analyst

Senior Business Intelligence Manager

Senior Business Intelligence Manager

Senior Business Intelligence Manager

Business Intelligence Developer

Lead Business Intelligence Analyst

Location: UK (Hybrid North West)

About the Role

We are seeking a Senior Business Intelligence Developer to join a small, high-impact data team. As the lead BI expert, you will work alongside a Data Analyst, IT Manager, Developer, and the CIO, taking ownership of Power BI development across the organisation. You will design and deliver visually compelling, high-quality dashboards and reports, optimise data models for performance, and establish BI best practices throughout the business.

This role involves close collaboration with stakeholders at all levels—from operational teams to executive leadership—translating business requirements into actionable, data-driven insights. While Power BI is the primary tool, experience with Looker or other BI platforms is a bonus but not essential.

This is a hands-on senior position, perfect for someone who enjoys applying technical expertise to create tangible business impact.

Key Responsibilities
  • Design, develop, and maintain intuitive, visually engaging Power BI dashboards and reports.
  • Communicate insights clearly, ensuring they are actionable for both technical and non-technical audiences.
  • Build efficient data models using star schema, slowly changing dimensions, and fact/dimension structures.
  • Optimise large datasets for performance using techniques such as query folding, incremental refresh, aggregations, and composite models.
  • Write and tune SQL queries across multiple platforms for maximum efficiency.
Governance & Standards
  • Define and maintain BI development standards, including naming conventions, workspace structures, and version control.
  • Implement and manage Row-Level Security (RLS) and Object-Level Security (OLS).
  • Establish a centralised semantic layer with consistent KPIs and measures.
Collaboration & Stakeholder Engagement
  • Partner with business leaders to gather reporting requirements and translate them into BI solutions.
  • Mentor and support analysts to enhance the overall BI capability of the team.
  • Act as the company’s go-to expert on BI best practices, providing guidance on tool strategy and adoption.
Data Integration
  • Work closely with IT and Data Engineering teams on data pipelines, ETL/ELT processes, and API integrations.
  • Ensure all BI solutions comply with GDPR and internal data governance standards.
  • Collaborate with the Data Analyst to provide guidance and develop BI skills.
  • Contribute to BI strategy and digital transformation initiatives alongside the CIO.
  • Partner with the IT Manager and Developer to maintain a robust and reliable data architecture.
Key Skills & Experience
  • 5+ years’ experience in BI development with strong Power BI expertise.
  • Advanced DAX, Power Query/M, and data modelling skills.
  • Strong SQL experience (SQL Server, Snowflake, or similar).
  • Proven ability to deliver user-friendly, visually compelling dashboards (portfolio required).
  • Excellent stakeholder management and communication skills.
  • Experience with Looker or other BI platforms.
  • Exposure to cloud data platforms (Snowflake, BigQuery).
  • Familiarity with ELT/ETL tools such as Fivetran or Kleene.
  • Understanding of data governance and GDPR compliance.
What We’re Looking For
  • A BI professional who combines deep technical expertise with a clear focus on business outcomes.
  • Someone who challenges assumptions and advocates for data-driven decision making.
  • A visual storyteller who produces clean, impactful dashboards.
  • A proactive senior hire capable of setting standards, taking ownership, and mentoring others.


#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.