Enterprise Data Architect London, Agile (Basé à London)

Jobleads
London
4 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Data Architect

Senior Data Architect

Senior Data Architect

Senior Data Architect

Senior Data Architect

Senior Data Architect

  • Work closely with the Privacy team to lead the design of data privacy and protection, and own the technical solution going forward.
  • Develop and deliver long-term strategic goals for data architecture vision and standards in conjunction with data users, department managers, clients, and other key stakeholders.
  • Create short-term tactical solutions to achieve long-term objectives and an overall data management roadmap.
  • Establish processes for governing the identification, collection, and use of corporate metadata; take steps to assure metadata accuracy and validity.
  • Establish methods and procedures for tracking data quality, completeness, redundancy, and improvement.
  • Conduct data capacity planning, life cycle, duration, usage requirements, feasibility studies, and other tasks.
  • Create strategies and plans for data security, backup, disaster recovery, business continuity, and archiving.
  • Ensure that data strategies and architectures are in regulatory compliance.

Acquisition & Deployment

  • Ensure the success of enterprise-level application rollouts (e.g. ERP, SCM, CRM, SAP, PeopleSoft, etc.).
  • Liaise with vendors and service providers to select the products or services that best meet company goals.
  • Design privacy data architecture which follows privacy retention standards.
  • Own the data obfuscation solution which will be applied across the estate.
  • Design blueprint data architectures, aligned to business function on both cloud and on-premise environments.
  • Develop and promote data management methodologies and standards, which may be executed.
  • Select and implement the appropriate tools, software, applications, and systems to support data technology goals.
  • Oversee the mapping of data sources, data movement, interfaces, and analytics, with the goal of ensuring data quality.
  • Collaborate with project managers and business unit leaders for all projects involving enterprise data.
  • Address data-related problems in regard to systems integration, compatibility, and multiple-platform integration.

What you will bring:

  • Certifications in Azure, and data virtualization tooling.
  • Certification in Snowflake.
  • This is a hands-on position in data architecture and design focused on data privacy, and will require a degree of data modelling and engineering. It is important the architecture understands data modelling standards and practices. They need to know GDPR and privacy regulations, and have applied automation processes when considering stale data.
  • Domain experience in reinsurance, actuarial or finance would be an advantage.
  • Knowledge and experience across Data Privacy and Protection, Data modelling, Data engineering, Analytics, Cloud Engineering, Data virtualization.
  • College diploma or university degree in computer science, information systems, or computer engineering.
  • Consulting mindset, who is comfortable working with our business, along with external vendors.

Who we are:

Enstar Group Limited (“Enstar” or “EGL”) is a leading global insurance group. Through our network of group companies, we help others – principally other insurance companies – release capital by taking over liability portfolios which no longer make strategic sense for them to hold. We create value by better managing these “run-off” insurance portfolios and strive to generate attractive risk-adjusted returns from our investment portfolio.

Enstar’s solutions allow our partners to release capital, dispose of non-core businesses and portfolios, achieve early finality on legacy insurance contracts and manage claims volatility. In return, Enstar drives earnings through savings arising from our technical excellence and from investment earnings on the reserves we hold.

At year-end 2023 we had completed 117 transactions since the 2000. Today, Enstar is the industry’s largest standalone run-off consolidator. With around 800 global employees, our network of group companies has a significant physical presence in Bermuda, where our headquarters are located, the United States, the United Kingdom, continental Europe, and Australia.

Enstar maintains a strong balance sheet. We hold long-term issuer ratings of BBB+ with stable outlook by S&P and Fitch. Enstar’s capital base continues to grow, reaching $7.4 billion at the end of 2023, including $5.6 billion of shareholders’ equity and total debt of $1.8 billion. A market leader in the run-off space, Enstar leverages its expertise in claims management, risk analysis, and investments to generate value. These services make Enstar different, something unique.

A characteristic that is core to our culture: we encourage an entrepreneurial spirit, our colleagues have autonomy to shape strategy, innovate new revenue streams and we reward those who are commercially focused.

NIMBLE

We are quick to respond to change. We embrace new technology and new lines of business according to market demands. We grasp new concepts quickly, are able to deliver in a timely manner and can improvise when needed.

SOLUTIONS FOCUSED

We are resilient, successful, have a winning mentality, possess a strong work ethic. We believe in getting it done.

TEAMWORK

Our strength is working together as a Group, across regions, companies and disciplines. We firmly believe the sum of our collective effort, knowledge and ambition will always outweigh our individual contributions. We work as a trusted partner to our clients.

AWARE

We use our knowledge and experience to stay aware of market trends, acquisition opportunities and other influencers that could impact us and our competitors. Our constant awareness means that we are vigilant, innovative and responsive.

RELEVANT

At all times we strive to undertake actions that are relevant to help us achieve our vision, and to ensure we remain a provider of relevant insurance solutions to the market. We have shown a capacity to evolve and will continue to do so in order to ensure our ongoing relevance to the market.

Equal Opportunities at Enstar:

Our annual Inclusivity Index puts Enstar ahead of the industry in terms of diversity and inclusivity. At Enstar, we value all types of diversity. We’re an equal opportunity employer and believe that our diversity creates an authentic working culture. We don’t discriminate on the basis of age, physical or mental disability, gender reassignment, marriage and civil partnership, pregnancy and carer status, race (including colour, nationality, and ethnic or national origin), religion or belief, sex and sexual orientation. Enstar is committed to providing an accessible recruitment experience for all those interested in working with us. Please let your Enstar Recruitment Partner know if you require any reasonable accommodation during the application process due to a disability to enable you to fully participate in our recruitment process.


#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.

Top 10 Best UK Universities for Data Science Degrees (2025 Guide)

Discover ten of the strongest UK universities for Data Science degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right programme for you. Data is the currency of the modern economy, and professionals who can wrangle, model and interpret vast datasets are in demand across every sector—from biotechnology and finance to sport and public policy. UK universities have been at the forefront of statistics, artificial intelligence and large-scale computing for decades, making the country a prime destination for aspiring data scientists. Below, we profile ten institutions whose undergraduate or postgraduate pathways excel in data science. Although league tables vary each year, these universities have a proven record of excellence in teaching, research and industry collaboration.

Veterans in Data Science: A Military‑to‑Civilian Pathway into Analytical Careers

Introduction The UK Government’s National AI Strategy projects that data‑driven innovation could add £630 billion to the economy by 2035. Employers across healthcare, defence, and fintech are scrambling for professionals who can turn raw data into actionable insights. In 2024 alone, job‑tracker Adzuna recorded a 42 % year‑on‑year rise in data‑science vacancies, with average advertised salaries surpassing £65k. For veterans, that talent drought is a golden opportunity. Whether you plotted artillery trajectories, decrypted enemy comms, or managed aircraft engine logs, you have already practised the fundamentals of hypothesis‑driven analysis and statistical rigour. This guide explains how to translate your military experience into civilian data‑science language, leverage Ministry of Defence (MoD) transition programmes, and land a rewarding role building predictive models that solve real‑world problems. Quick Win: Take a peek at our live Junior Data Scientist roles to see who’s hiring this week.

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.