Senior Data/BI Analyst

East Horndon
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data analyst

Data Analyst

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior AWS Data engineer (LDW Data Warehouse Discovery)

Senior Data/BI Analyst

Location: Essex (Hybrid – 3 days onsite)
Salary: Up to £70,000

A growing company in the manufacturing and engineering sector is transforming how it leverages data. Their Business Relationship Model (BRM) is a powerful relational database connecting all areas of the business, providing real-time insights and historical context on customer and supplier relationships. This system is key to unlocking new revenue opportunities by identifying patterns and connections within their data.

They are looking for a highly skilled Data Analyst to help structure and optimize this evolving data framework, uncovering hidden commercial opportunities from complex data interactions. The ideal candidate will have strong technical expertise (Python, SQL, Power BI) and the ability to communicate insights clearly to non-technical stakeholders.

What You’ll Be Doing:

  • Extracting & structuring data: Work with large, complex datasets from multiple sources (including the by-products of ERP systems) to generate actionable commercial insights.
  • Identifying business opportunities: Analyze interactions between part types, customers, and manufacturing sources to uncover trends that drive revenue.
  • Creating data-driven strategies: Support procurement, sales, and finance teams by translating insights into clear business recommendations.
  • Enhancing data frameworks: Help evolve and structure the BRM system to improve real-time decision-making.
  • Supporting key projects: Work on two major data-driven initiatives, ensuring data integrity and providing analytical support.
  • Communicating insights: Present findings in layman’s terms to leadership and cross-functional teams, making complex data easy to understand.

    What We’re Looking For:
  • Minimum 3 years of experience in data analysis (or exceptional skills if less).
  • Technical expertise: Strong in Python, SQL, Power BI (experience with relational databases is a plus).
  • Industry background: Preferred experience in engineering, manufacturing, aerospace, or similar complex industries, but adaptable candidates from pharmaceuticals, nuclear, or other sectors will be considered.
  • Problem-solving mindset: Ability to connect data points, recognize trends, and provide commercially viable solutions.
  • Strong communication skills: Comfortable presenting insights to non-technical stakeholders in an actionable way.
  • Self-motivated & proactive: Can hit the ground running, work independently, and collaborate with multiple teams.

    Why Join Us?
  • Drive data transformation in a company evolving its analytical capabilities.
  • Work cross-functionally with leadership, procurement, sales, finance & project teams.
  • Impact business strategy by uncovering hidden commercial opportunities.
  • Hybrid setup – 3 days onsite in Essex, 2 days remote.
  • Competitive salary up to £70,000.

    Interview Process:
  1. 30-minute call with a senior leader.
  2. Final 1-hour interview with senior leadership.
  3. Offer & onboarding

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.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.