Principal Engineer - Central Data Team

Workonblockchain
Bolton
2 months ago
Applications closed

Related Jobs

View all jobs

Principal Software Engineer

Data Analyst

Principal MLOps Engineer - Chase UK

Principal Data Engineer

Principal Data Scientist / AI Engineer

Senior Machine Learning Engineer

Principal Engineer - Central Data Team
Salary: 47,000 - 47,000 GBP per year

At MBDA we are looking for a Data engineer!


Our tech stack:
ERP, Support, SAP, Security


Requirements:
We are looking for an engineer with experience in ERP systems. A minimum qualification of HNC or equivalent is necessary, and an APICs supply chain certification would be desirable but not essential. It is essential to have experience using ERP systems, and experience with SAP will be beneficial. We value strong analytical and problem-solving skills, attention to detail, and a proven track record of managing and implementing process improvements.


Your responsibilities are:
As a Principal Engineer within our Central Data team, you will ensure the effectiveness of tools, processes, and policies in place. You will define and manage audit strategies in line with the master data policy, collaborating with wider engineering and planning teams to drive improvements and standardization. Your responsibilities will include:

  1. Utilizing SAP to extract, understand, and interpret data, effectively communicating the causes and effects based on actions and decisions taken.
  2. Reviewing engineering processes to ensure alignment and robust MRP outputs.
  3. Providing first-line support for daily issues.
  4. Promoting data integrity across the ERP environment through involvement in the Operational Excellence master data work stream.
  5. Generating and distributing KPI packs.
  6. Creating and executing auditing strategies for master data, including material masters, BOMs, and routings.
  7. Implementing processes for inputting routing times into SAP to enhance capacity and scheduling functionality.
  8. Developing new assembly structures in collaboration with cross-functional business teams to implement process improvements that support SAP usage and customer delivery.
  9. Creating and reviewing detailed requirement analysis documents and functional specifications based on business requirements.
  10. Working with outsourced support partners to develop, implement, test, and support enhancements to the SAP system, including training for the wider business.
  11. Conducting system regression testing for new releases or upgrades and maintaining SAP user guides.

Location:Bridgewater Avenue, Manchester, United Kingdom

Benefits & perks that we offer:
We offer a competitive salary, circa £47,000 depending on experience, and a company bonus of up to £2,500 based on company performance. Our dynamic hybrid working arrangement allows for 3 to 4 days on-site per week. We value our employees and offer a maximum pension contribution of up to 14%, opportunities for paid overtime, up to 15 additional days of flexi leave, and flexible working arrangements. Our enhanced parental leave policies provide up to 26 weeks for maternity, adoption, and shared parental leave, with additional enhancements for paternity leave, neonatal leave, and fertility treatments. Our fantastic site facilities include subsidized meals, free car parking, and more.

At MBDA, we are a leading defense organization, proud to support the Armed Forces in defending our freedom. We recognize the uniqueness of every individual and encourage you to reach out for any advice, support, or adjustments needed throughout the recruitment process. We are committed to diversity and inclusion and have various employee-led networks supporting this initiative.

#J-18808-Ljbffr

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.

Jobs

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Jobs Careers

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.