[EMEA] - Data Architect (Basé à London)

Jobleads
London
11 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst - Sales Operations

We aretech transformationspecialists, uniting human expertise with AI to create scalable tech solutions.

With over 6,500 CI&Ters around the world, we’ve built partnerships with more than 1,000 clients during our 30 years of history. Artificial Intelligence is our reality.

When applying for one of our positions, you’re agreeing to the use of AI in the early phases of the selection process, where your profile will be evaluated by our virtual assistant. For more information, access our opportunities’ page.

Key Responsibilities

  1. Design and implement robust data architectures using Data Bricks and cloud platforms (AWS, Azure).
  2. Collaborate with clients to understand their data needs and provide tailored solutions.
  3. Lead pitches and presentations to potential clients, clearly articulating our value proposition.
  4. Work hands-on with the team to create innovative solutions to complex data issues.
  5. Stay updated with the latest trends in data architecture and financial services to provide thought leadership.
  6. Mentor junior team members and foster a culture of continuous improvement.

Requirements

  1. Proven experience as a Data Architect with a strong background in data management and architecture.
  2. Demonstrated experience with Data Bricks and cloud technologies such as AWS or Azure.
  3. A solid career trajectory within data roles, showcasing growth and expertise.
  4. Strong client-facing skills with a track record of successful client engagement.
  5. Experience in leading pitches and engaging stakeholders effectively.
  6. Hands-on mentality with a passion for problem-solving and creating actionable solutions.
  7. Experience within the financial services industry is a distinct advantage.

What We Offer

  1. Competitive salary and benefits package.
  2. Opportunity to work with a talented team and industry leaders.
  3. A dynamic and supportive work environment that encourages innovation and growth.
  4. Professional development opportunities to further enhance your skills.

Collaboration is our superpower, diversity unites us, and excellence is our standard.

We value diverse identities and life experiences, fostering a diverse, inclusive, and safe work environment. We encourage applications from diverse and underrepresented groups to our job positions.


#J-18808-Ljbffr

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.

Jobs

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

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.

🍪 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.