Data Architect

MBN Solutions
Edinburgh
1 month ago
Applications closed

Related Jobs

View all jobs

Data Architect - Security Cleared

Data Architect

Data Architect | Research Analytics

Data Architect

Data Architect

Data Architect (Hybrid) - Contract London, England, United Kingdom (Basé à London)

Data Architect – Edinburgh (Hybrid)


Step into a Data Architect Role – Risk & Finance Data Architect


Are you an experienced data professional looking for your next challenge? If you’ve been working with data architecture, data modelling, or solution design and are ready to take the step into aData Architectrole, this opportunity is for you.


You'll play a key role in defining and shaping high-level data architecture for our client’s Risk & Finance domain, working closely with platform and domain teams to design solutions that drive business success. This is a fantastic chance tobuild on your existing technical expertise, develop your architectural skills, and grow within a supportive and collaborative team.


What You’ll Do


As part of our architecture team, you’ll:

  • Take your first step into a Data Architect role (if you aren’t a Data Architect already), with support and mentorship to develop your skills.
  • Help shape technical data architecture and solution designthat align with our long-term strategy.
  • Collaborate with teams across the business, ensuring solutions are scalable and effective.
  • Work on end-to-end solution designs, contributing to architecture that spans multiple platforms.
  • Own technical data design challenges, helping to drive practical and effective solutions.
  • Learn and apply enterprise architecture principles, data mesh concepts, and event-driven architectures.
  • Stay up to date with emerging technologies, contributing ideas that improve our data capabilities.


What You’ll Need


This role is ideal for someone whohas experience in data architecture, data modelling, or solution designand is ready to progress into a Data Architect position.


We’re looking for someone with:

  • A background in data, application, or solution architecture, with an interest in stepping up into a Data Architect role (if you aren’t already a Data Architect)
  • Experience working with data modelling, data integration, or database design.
  • Familiarity with industry frameworkssuch as TOGAF or ArchiMate (experience is a plus but not essential).
  • An understanding of Agile methodologies and modern software development approaches.
  • A problem-solving mindsetand the ability to communicate complex technical concepts clearly.
  • A willingness to learn and develop your architectural skillsin a supportive environment.

Why Join Us?

  • A structured pathway into a Data Architect role, with support and development opportunities.
  • Exposure toreal-world architectural challengesin a high-impact business domain.
  • The chance to work onexciting, large-scale data solutionsthat make a real difference.
  • A collaborative and forward-thinking environment whereyour growth is valued.

If you're ready totake the next step in your data career and transition into a Data Architect role, we'd love to hear from you.

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 Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Jobs

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

🍪 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.