Head of Development

Bridewell Consulting
Cardiff
1 year ago
Applications closed

Related Jobs

View all jobs

Data Architect / Head of Data / Head of Development

Data Engineer (18 Months FTC)

Data Engineer (18 Months FTC)

Data Governance Analyst

Head of Data Compliance

Head of Data Engineering (AI)

About Bridewell
One of the most exciting prospects in the UK cyber security sector today, Bridewell is a leading cyber security services company specialising in protecting and transforming critical business functions for some of the world's most trusted organisations. We are the trusted partner for operators of essential services and provide end-to-end cyber security capabilities that help our clients overcome their security challenges, allowing them to operate safely and securely. Our customer-centric approach, commitment to excellence, and emphasis on innovation keep us at the forefront of the market.

Bridewell holds the Gold level, Investors in People award which we feel solidifies and reflects on the outstanding calibre that makes us truly one team.

Who are we looking for?
As part of our growth journey, we are seeking a highly skilled and dynamic Head of Development to lead our engineering teams to the next level. This is a unique opportunity to shape our technology and product delivery practices in an environment that values agility, collaboration, and innovation.

As the Head of Development, you will play a pivotal role in driving the technical excellence, scalability, and agility of our product development lifecycle. Reporting directly to the CTO, you will lead a multi-disciplinary engineering team, ensuring the seamless integration of disciplines such as data engineering, DevOps, development, testing, and architecture.

You will also work closely with Product Management to ensure that our solutions remain customer-focused and market-leading. In addition, you will leverage your experience in building or managing near-shore and partner-augmented teams to help scale the engineering organization effectively and sustainably. This role is ideal for someone with a strong technical foundation who thrives in scaling and maturing engineering teams within a disciplined agile framework.

Key responsibilities:

  • Build, scale, and lead high-performing, multi-disciplinary teams (data engineering, DevOps, development, testing, and architecture).
  • Foster a culture of collaboration, innovation, and continuous improvement across teams.
  • Attract and retain top talent, ensuring diversity and inclusion are central to team growth strategies.
  • Establish and manage partnerships with near-shore or partner-augmented teams to support scaling needs and project delivery.
  • Drive the adoption and maturity of Disciplined Agile Delivery (DAD) practices across the engineering organization.
  • Ensure disciplined, predictable, and customer-focused software delivery cycles.
  • Collaborate with teams to design, build, and maintain robust systems and solutions using .Net, Python, and React (or equivalent technologies).
  • Leverage expertise in Machine Learning (ML) and Artificial Intelligence (AI) to deliver innovative solutions.
  • Continuously improve the software development lifecycle (SDLC) to enhance quality, scalability, and speed of delivery.
  • Implement best practices in testing, development, and architecture to ensure a high standard of technical excellence.
  • Partner closely with Product Management to ensure alignment between technical delivery and customer needs.
  • Ensure product roadmaps are executed with agility and deliver tangible value to customers.


What we're looking for
We're looking for someone with a proven track record of building and scaling engineering teams and delivering exceptional products. You'll be a hands-on, strategic thinker who values collaboration and understands how to create an environment where people thrive.

  • Strong engineering background in disciplines such as data science, software development, testing, or DevOps.
  • Experience of building and managing a near shore development team.
  • Experience scaling and leading multi-disciplinary teams, including architecture, testing, data engineering, development, and DevOps.
  • Proven experience in building or managing near-shore and/or partner-augmented teams to meet scaling and delivery goals.
  • In-depth understanding of and experience with the Disciplined Agile Delivery (DAD) framework, with a relevant qualification preferred.
  • Familiarity with Machine Learning (ML) and Artificial Intelligence (AI) technologies and their practical applications.
  • Proven ability to mature SDLC capabilities in fast-paced, growth-focused organizations.
  • Hands-on experience with .Net, Python, and React (or similar technologies) is highly desirable.
  • Excellent communication and leadership skills, with a focus on fostering collaboration and inclusion.
  • A customer-focused mindset with the ability to integrate technical excellence with business priorities.


Why Join Us?
Our vision is to create a safe, inclusive digital world where people and organisations can thrive. Our values ofDo the Right Thing, One Team and Above and Beyondemphasises the importance of the part we play in society, and our commitment to our people and clients. Our story to-date has been phenomenal, but success doesn't end here and as we continue to grow and scale, we want to keep the same culture, passion and commitment to high quality that has enabled us to get this far. Bridewell will provide a great career opportunity with continual development as well as the following:

  • 25 Days Holiday - Plus buy and sell options 
  • Flexible Working (around core office hours) 
  • Performance Incentive Bonus 
  • Company Pension 
  • Employee Shareholder Scheme 
  • Personal Day & Birthday Off - After 1 year of service 
  • Family Leave - After 1 year of service 
  • Enhanced Maternity based on length of service 
  • Dedicated Training Budget 
  • Life Assurance 
  • Electric Vehicle Scheme & Cycle to Work Scheme
  • Private Healthcare (incl. Gym discounts and vison care)


Location: Bridewell operates a hybrid and flexible working policy, however you will be required to travel to different sites on occasion.

Note: To be eligible for this job you must either hold SC or be eligible and willing to go through security clearance.

Bridewell values diversity in the workplace and is a fair and equal opportunity employer. We are committed to creating an equal and inclusive working environment, with the aim that our employees will be truly representative of all sections of society and each person feels respected and able to give their best.

YXJjaGllLmhvbG1lcy4xMjI3OS4xMjI3MUBicmlkZXdlbGxjb25zdWx0aW5nLmFwbGl0cmFrLmNvbQ.gif

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.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 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.