Junior Enterprise Architect

PA Consulting
London
4 months ago
Applications closed

Related Jobs

View all jobs

Enterprise Data Architect

Data & Analytics Practice:-Data Architect role- Junior level (Basé à London)

Data & Analytics Practice:-Data Architect role- Junior level

Principal Data Analyst

Principal Security Data Analyst

Principal Data Analyst

Job Description

 

  • Develop and implement an enterprise architecture strategy that aligns IT and business goals. 

  • Define and document technology standards, principles, guidelines, and best practices to ensure consistency across the enterprise. 

  • Lead the design of technology solutions that meet business requirements, and ensure their scalability, security, and sustainability.

  • 2.Stakeholder Collaboration: 

  • Collaborate with business leaders and IT teams to understand business processes, challenges, and technology needs. 

  • Act as a liaison between technical teams and business units to ensure that the technology architecture meets current and future needs. 

  • Provide guidance and consultation to project teams on all aspects of architecture, ensuring alignment with enterprise standards. 

  • Technology Road mapping and Solution Architecture: 

  • Develop and maintain a multi-year technology roadmap aligned with business strategy and priorities. 

  • Identify emerging technology trends and evaluate their potential impact on the organisation. 

  • Define solution architecture for specific initiatives or projects, ensuring compatibility and compliance with the enterprise architecture. 

  • Governance and Compliance: 

  • Establish and enforce enterprise architecture governance processes to ensure compliance with internal and external policies and regulations. 

  • Evaluate and monitor existing and planned systems for alignment with enterprise architecture standards. 

  • Define key performance indicators (KPIs) and metrics to assess the health and performance of enterprise architecture initiatives. 

  • Risk Management: 

  • Identify potential technology risks and develop mitigation strategies to address these risks. 

  • Conduct regular assessments of technology architecture to identify areas for improvement, cost reduction, and increased efficiency. 

  • Work closely with cybersecurity teams to ensure that architecture solutions adhere to security standards and best practices. 

  • Data Architecture and Integration: 

  • Design and implement data architecture that supports enterprise-wide data analytics, reporting, and decision-making. 

  • Ensure integration between systems and data sources to improve the accessibility and reliability of data across the organisation. 

  • Define data governance standards and practices to ensure data quality, security, and compliance. 

  • Documentation and Communication: 

  • Maintain comprehensive documentation of the enterprise architecture, including system designs, technology standards, and architecture models. 

  • Regularly communicate architecture status, risks, and recommendations to senior leadership. 

  • Provide training, support, and guidance to IT teams to help them adhere to enterprise architecture standards. 

 


Qualifications

Technical Skills: 

  • Proven track record in designing and implementing enterprise architectures in complex organisations. 

  • Experience in various architectural domains: business, application, data, and technology. 

  • Strong knowledge of enterprise architecture frameworks (e.g., TOGAF). 

  • Proficiency in architectural modeling tools (e.g., ArchiMate, Sparx, or similar). 

  • Familiarity with cloud platforms (AWS, Azure, Google Cloud) and integration technologies (APIs, SOA, microservices). 

  • Knowledge of cybersecurity best practices and regulatory compliance (e.g., GDPR).

Soft Skills: 

  • Excellent analytical, problem-solving, and decision-making skills. 

  • Strong communication and presentation skills, with the ability to explain complex concepts to non-technical stakeholders. 

  • Ability to work collaboratively with cross-functional teams and manage multiple priorities. 

  • Strategic thinker with a proactive approach to identifying and addressing challenges. 



Additional Information

Life At PA encompasses our peoples' experience at PA. It's about how we enrich peoples’ working lives by giving them access to unique people and growth opportunities and purpose led meaningful work.

We believe diversity fuels ingenuity. Diversity of thought brings exciting perspectives; diversity of experience brings a wealth of knowledge, and diversity of skills brings the tools we need. When we bring people together with diverse backgrounds, identities, and minds, embracing that difference through an inclusive culture where our people thrive; we unleash the power of diversity – bringing ingenuity to life. We are dedicated to supporting the physical, emotional, social and financial well-being of our people.

We are currently operating a discretionary hybrid working model which is designed to help you plan your work and your life. We want our people to come into the office at least two days a week.

Check out some of our extensive benefits:

• Health and lifestyle perks accompanying private healthcare for you and your family

• 25 days annual leave (plus a bonus half day on Christmas Eve) with the opportunity to buy 5 additional days

• Generous company pension scheme

• Opportunity to get involved with community and charity-based initiatives

• Annual performance-based bonus

• PA share ownership

• Tax efficient benefits (cycle to work, give as you earn)

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 Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

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

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

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.