Bi Developer

Manchester
1 month ago
Applications closed

Related Jobs

View all jobs

BI Developer

Bi Developer

Power BI Developer Contract role. Crewe, £350 per day

Power BI Developer

Power BI Developer

Power BI Developer

BI Analyst / BI Developer

SQL sharp-shooter?
Know your way around Power BI and can turn raw data into real impact?
Let’s talk.

We’re looking for a BI Analyst / Developer to join a growing business that’s smashing it year after year — doubling turnover, growing teams, and levelling up their tech.

Based in Manchester (with hybrid flexibility), this is a chance to get stuck into meaningful work, not just crunch numbers.

You’ll be working closely with the Data Manager and key business users to build slick, user-friendly reports that actually help people do their jobs better. Think paginated reports that give teams exactly what they need, when they need it — with clarity and precision.

You’ll need solid SQL skills (queries + stored procedures), and experience with SSRS report building. Power BI is also part of the mix, so any dashboards or visualisation experience is a bonus.

What you'll be working with:
• SQL — writing, optimising, and making it sing
• SSRS — building paginated reports that people love using
• Power BI — dashboarding and data storytelling
• Excel or QlikView — nice to have, but not essential

This is a role where you’re not just sat behind a screen — you’ll be talking to people across the business, understanding what they need, and turning that into clean, useful, easy-to-digest data. You’ll have a voice, space to bring ideas, and be part of shaping how the team works.

What’s in it for you?
• Up to £50,000 salary
• Pension
• Hybrid working (Manchester HQ) - More remote than onsite
• A down-to-earth, supportive team

If you’re looking for a BI role where you can grow, be heard, and make a real difference — drop us your CV and let’s chat

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Quantum-Enhanced AI in Data Engineering: Reshaping the Big Data Pipeline

Data engineering has become an indispensable pillar of the modern technology ecosystem. As companies gather massive troves of data—often measured in petabytes—the importance of robust, scalable data pipelines cannot be overstated. From ingestion and storage to transformation and analysis, data engineers stand at the forefront of delivering reliable data for analytics, machine learning, and critical business decisions. Simultaneously, the field of Artificial Intelligence (AI) has undergone a revolution, transitioning from niche research projects to a foundational tool for everything from predictive maintenance and fraud detection to customer experience personalisation. Yet as AI models grow in complexity—think large language models with hundreds of billions of parameters—the data volumes and computational needs escalate dramatically. The industry finds itself at an inflection point: traditional computing systems may eventually hit performance ceilings, even when scaled horizontally with thousands of nodes. Enter quantum computing, a nascent yet rapidly progressing technology that leverages quantum mechanics to tackle certain computational tasks exponentially faster than classical machines. While quantum computing is still maturing, its potential to supercharge AI workflows—often referred to as quantum-enhanced AI—has piqued the curiosity of data engineers and enterprises alike. This synergy could solve some of the biggest headaches in data engineering: accelerating data transformations, enabling more efficient analytics, and even facilitating entirely new kinds of modelling once believed to be intractable. In this article, we explore: How data engineering has evolved to support AI’s insatiable appetite for high-quality, well-structured data. The fundamentals of quantum computing and why it may transform the data engineering landscape. Potential real-world applications for quantum-enhanced AI in data engineering—from data ingestion to machine learning pipeline optimisation. Emerging career paths and skill sets needed to thrive in a future where data, AI, and quantum computing intersect. Challenges, ethical considerations, and forward-looking perspectives on how this convergence might shape the data engineering domain. If you work in data engineering, are curious about quantum computing, or simply want to stay on the cutting edge of technology, read on. The next frontier of data-driven innovation may well be quantum-powered.

Data Engineering Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data. It’s the critical lifeblood of every forward-thinking organisation, fueling everything from strategic decision-making to real-time analytics. As data volumes skyrocket and technologies mature, the UK has distinguished itself as a frontrunner in data innovation. A robust venture capital scene, government-backed initiatives, and a wealth of academic talent have created fertile ground for data-centric start-ups across the country. In this Q3 2025 Investment Tracker, we’ll delve into the newly funded UK start-ups shaping the future of data engineering. More importantly, we’ll explore the rich job opportunities that have emerged alongside these funding announcements. From building scalable ETL (Extract, Transform, Load) pipelines to architecting data warehouses and implementing advanced data governance frameworks, data engineers, architects, and analysts have an incredible array of roles to pursue. If you’re eager to elevate your career in data engineering, read on for insights into the most dynamic start-ups, their fresh capital injections, and the skill sets they’re hungry for.

Portfolio Projects That Get You Hired for Data Engineering Jobs (With Real GitHub Examples)

Data is increasingly the lifeblood of businesses, driving everything from product development to customer experience. At the centre of this revolution are data engineers—professionals responsible for building robust data pipelines, architecting scalable storage solutions, and preparing data for analytics and machine learning. If you’re looking to land a role in this exciting and high-demand field, a strong CV is only part of the puzzle. You also need a compelling data engineering portfolio that shows you can roll up your sleeves and deliver real-world results. In this guide, we’ll cover: Why a data engineering portfolio is crucial for standing out in the job market. Choosing the right projects for your target data engineering roles. Real GitHub examples that demonstrate best practices in data pipeline creation, cloud deployments, and more. Actionable project ideas you can start right now, from building ETL pipelines to implementing real-time streaming solutions. Best practices for structuring your GitHub repositories and showcasing your work effectively. By the end, you’ll know exactly how to build and present a portfolio that resonates with hiring managers—and when you’re ready to take the next step, don’t forget to upload your CV on DataEngineeringJobs.co.uk. Our platform connects top data engineering talent with companies that need your skills, ensuring your portfolio gets the attention it deserves.