BI Consultant

Reading
11 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Lead Data Engineer

Housing Data Engineer

BI Data Analyst

Data Analyst (Engineering)

Data Analyst

Job Title: BI Consultant
Location: Remote (UK-based)
Salary: Up to £65,000

About My Client

My client is a family-owned and operated Microsoft Partner specialising in Data Analytics, Data Platforms, Business Intelligence (BI), Data Management, and Data Strategy. With a successful track record spanning nearly 30 years, they have built a strong reputation for delivering high-quality solutions and fostering long-term client relationships. Additionally, they offer technical training services, particularly in Power BI.

Operating with a close-knit team of around ten professionals, including Consultants, Sales, and Trainers, my client provides an environment where collaboration and professional growth are encouraged. The company is led by the Managing Director, and supported by Lead Technical Consultant, both of whom remain actively involved in projects and decision-making.

Role Overview

As a BI Consultant, you will be involved in the full project life-cycle, engaging directly with clients to understand their needs, develop solutions, and provide ongoing support. This is a hands-on role requiring strong technical skills and the ability to manage stakeholder relationships effectively. While the focus is on consulting, there are opportunities to contribute to my client's training arm if desired.

Projects will vary and may include:

Power BI implementation

Azure Data migration

Cloud data engineering

Key Responsibilities

Work end-to-end on BI projects, from requirements gathering to post-project support

Develop and implement Data Warehouses (DWH)

Utilise SQL for data management and optimisation

Design and develop Power BI reports and dashboards

Collaborate with clients to ensure solutions align with business needs

Ensure a strong understanding of the "why" behind data solutions, focusing on delivering value beyond technical implementation

Required Skills & Experience

Solid experience in end-to-end BI development

Proven expertise in Data Warehouse development

Strong SQL skills

Hands-on experience with Power BI

Azure expertise (preferred for higher salary consideration)

Relevant industry certifications

Who We're Looking For

The ideal candidate is not just technically proficient but also possesses strong stakeholder management and communication skills. My client values individuals who are passionate about data and eager to help clients unlock its full potential. A consultant mindset is essential this role is not suited for SQL DBAs or candidates whose primary experience is in data analysis rather than back-end development.

Salary, Benefits & Working Pattern

Salary: Up to £60,000 (£65,000 for candidates with strong Azure experience)

Location: Remote (UK-based) with occasional travel for client site visits (rare) and team meet-ups a few times a year

Holidays: 25 days plus bank holidays

Pension: Employer contribution of 3%, Employee contribution of 5%

Private Health Cover

This is an excellent opportunity to join a company that values its employees, fosters a positive work environment, and provides exposure to exciting and impactful data projects. If you're looking for a role where you can grow professionally while making a real difference for clients, this could be the perfect fit! If you are interested in this role or know someone who would be a great fit apply now or reach out to me @(url removed)

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.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.