Director of Data and AI

Exquitech Group
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Manager, Data Science - eBay Live

Senior Data Scientist

Vice President, Head of Discovery Data Science

Western Europe Practice Head - Data Science (Machine Learning/Artificial Intelligence (ML/AI)

Director, Machine Learning Science - Recommendations & Relevance

Director, Data Science - Measurement & Optimization

Company Description


Exquitech Group is a multinational technology company specializing in developing innovative Cloud-based solutions and services for clients worldwide. With a mission to empower organizations through technology, Exquitech drives innovation, productivity, and digital transformation. As a Tier One Microsoft Partner with numerous awards and advanced specializations, Exquitech serves over 2,000 customers globally and has a strong presence in key markets.


Role Description


This is a full-time hybrid role for a Data and AI Director at Exquitech Group in the London Area, United Kingdom. The Data and AI Director will lead and oversee the Data Department and the AI Department, ensuring the development, deployment, and maintenance of cutting-edge data and AI technologies. This role includes managing and expanding the department’s strategic initiatives across various regions, fostering innovation in data warehousing, machine learning, large language models (LLMs), and other advanced AI solutions. The ideal candidate will be responsible for pre-sales and solution architecture activities and will manage departmental budgeting and strstegic growth to support the organization’s growth.


Qualifications


  • Data Governance, Data Management, and Data Quality skills
  • Analytical Skills
  • Clinical Data Management experience
  • Proven track record in leading data and AI initiatives
  • Strong understanding of cloud-based technologies
  • Excellent leadership and communication skills
  • Advanced degree in Data Science, Computer Science, or related field
  • Certifications in Data Management or AI are a plus


Key Responsibilities:


Leadership and Management:


  • Lead, mentor, and manage the teams within the Data and AI Departments.
  • Establish a vision for the department and drive its strategic expansion across multiple regions.
  • Oversee end-to-end project delivery and ensure alignment with the company’s goals and standards.


Technical Oversight:


  • Oversee the development and maintenance of Microsoft Data Warehousing solutions on Fabric and other data management platforms.
  • Lead initiatives involving Databricks for data processing, machine learning, and big data analytics.
  • Drive the integration and utilization of Azure OpenAI services and other advanced machine learning technologies.
  • Manage the development and implementation of machine learning models, including LLMs and AI-driven solutions to support business objectives.
  • Pre-Sales and Solution Architecture:
  • Support pre-sales activities, engaging with clients to understand their needs and propose effective data and AI solutions.


  • Design and review solution architectures to ensure robust, scalable, and cost-effective deployments.
  • Collaborate with sales and marketing teams to position data and AI solutions effectively in the market.
  • Strategic Planning and Budgeting:
  • Develop and manage departmental budgets, ensuring optimal allocation of resources for project success and profitability.
  • Develop strategies to grow the department


  • Collaborate with the executive team to align departmental plans with the overall organizational strategy.


Cross-Regional Coordination:


  • Work across regions to align data and AI strategies, ensuring consistent delivery and adherence to global standards.
  • Foster partnerships and relationships with regional stakeholders to drive the adoption of the company’s solutions.


Innovation and Continuous Improvement:


  • Stay updated on industry trends and emerging technologies in data and AI.
  • Promote a culture of continuous learning and improvement, ensuring teams are equipped with the latest tools and knowledge.
  • Drive the adoption of best practices in data governance, security, and compliance.


Qualifications:


  • Bachelor’s degree in Computer Science, Data Science, AI, or a related field; Master’s or Ph.D. preferred.
  • 10+ years of experience in data management, AI development, or related fields, with 5+ years in a leadership role.
  • Expertise in Microsoft Data Warehousing on Fabric, Purview, Databricks, Azure OpenAI, and other AI technologies.
  • Strong experience with machine learning models, LLMs, and solution architecture.
  • Proven track record in pre-sales, client engagement, large project implementation, and strategic planning.
  • Demonstrated ability to manage and expand teams across multiple regions.
  • Excellent budgeting and resource management skills.
  • Strong leadership, communication, and interpersonal skills.

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

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

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.