Data Architect

Egis Group
Dartford
11 months ago
Applications closed

Related Jobs

View all jobs

Data Engineering Director

Data Engineering Director

Data Engineering Leader: Scale & Architect Platforms

GCP Data Architect & Big Data Engineer

Lead Data Engineer / Architect – Databricks Active - SC Cleared

Senior Data Engineer: Architect Scalable Data Platforms

Job Description

We’ve formed a Joint Venture project called Connect Plus Services (CPS) to work with our partners to widen, operate and maintain the M25 under a 30-year contract and are looking for Data Architect to develop, manage and lead our corporate data strategy. As a data architect you’ll be crucial in delivering solutions for the digital data lake in project and you’ll be pivotal in supporting and enhancing our newly established data governance framework.

As a Data Architect, you’ll be crucial in delivering solutions for the Digital Data Lake in the JV. You’ll develop solutions for specific business needs, understand business requirements, and review solution impacts. You will be accountable for the data architecture of the M25 IT systems and a roadmap of activities aligned with architectural principles to improve long-term architecture. We are looking for a self-starter who can work independently while collaborating with business teams as needed.

 

Key responsibilities:

Develop and lead data strategy:

  • Formulating and executing a comprehensive corporate-level data strategy that aligns with business objectives and drives organisational growth.
  • Identify opportunities for leveraging data to achieve business goals and enhance operational efficiency.
  • Data Modelling for Business Intelligence:
    • Design, develop, and maintain complex data models to support business intelligence initiatives, with a strong focus on Power BI reporting.
    • Ensure data models are scalable, reliable, and optimised for performance to facilitate insightful and actionable business analytics

Data Governance:

  • Collaborate with cross-functional teams to support the implementation and ongoing management of the data governance framework.
  • Define and enforce data governance policies, standards, and best practices to ensure data quality, consistency, and security.
  • Strategic Thinking and Decision Influence:
    • Provide strategic insights and recommendations to influence data-related decisions at the corporate level.
    • Partner with senior leadership to integrate data strategy into broader business strategies and initiatives.

Stakeholder Engagement:

  • Engage with key stakeholders to understand data needs, gather requirements, and deliver tailored data solutions.
  • Communicate complex data concepts and strategies to non-technical audiences in a clear and compelling manner.


Qualifications

  • A previous experience of coordination of small technology teams
  • Capability to understand and pre-empt business requirements.
  • Capability of translating business requirements in technology solutions
  • Presenting skills.
  • Engaging senior level stakeholders and obtaining buy-in.
  • Proven experience in developing and leading corporate-level data strategies.
  • Extensive hands-on experience with complex data modelling, particularly for Power BI reports.
  • Strong strategic thinking and problem-solving skills, with the ability to influence data-related decisions at the highest levels.

The following technologies are essential, and a good familiarity is required, including development methodologies and related programming languages (SQL, scripting) skills.

  • Amazon AWS environment.
  • Redshift
  • Power BI (authoring and administration)
  • MS SQL Server family (development and administration)
  • Fundamentals of networking and Microsoft Entra ID

Familiarity with the following technologies is desirable but not essential.

  • Power Apps
  • ESRI ArcGis
  • Microsoft 365 Platform
  • Lambda
  • R or Phyton for data science



Additional Information

You must have the right to work in the UK, we are unable to provide sponsorship for this role.

Equality, Diversity & Inclusion

We are an Equal Opportunities Employer and we strive to build a workforce that truly reflects the communities we represent. We welcome candidates from all backgrounds, regardless of age, disability, gender, gender identity, gender expression, race, religion or belief, sexual orientation, socioeconomic background, and any other protected characteristic. If you decide to apply for an opportunity with us, your application will be assessed based purely on your experience, the essential and desirable criteria, and your suitability for the role. We value each and every one’s contribution as this builds our culture and means that if you work with us, you will be included, listened to, and respected.

 

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.

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

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

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

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.