Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Enterprise Data Architect

Tenth Revolution Group
London
9 months ago
Applications closed

Related Jobs

View all jobs

Enterprise Data Architect - VP

Enterprise Data Architect

Enterprise Data Architect -Risk, Hybrid (1d/w Birmingham) Outside IR35

Enterprise Data Architect – Azure / Snowflake

Oracle Fusion Lead Enterprise Data Architect

Data Architect / Data Modeler Contract

Job Description

Job Title: Enterprise Data Architect

About the Role


My client is seeking an Enterprise Data Architect to play a pivotal role in shaping and delivering a forward-looking data strategy that supports their transformation goals and aligns with their strategic plan for 2030. The successful candidate will lead a team to optimise data infrastructure, focusing on Master Data Management, big data, AI, and performance reporting.

The role involves designing and implementing enterprise data architecture, driving governance and security frameworks, and ensuring the development of actionable insights through performance monitoring and reporting.

This position offers the opportunity to provide inspirational leadership to cross-functional teams, deliver strategic outcomes, and establish a culture of professionalism and commercial awareness.



Key Responsibilities

Enterprise Data Strategy and Architecture

  • Develop and implement an enterprise-wide data strategy, integrating varied data sources and analytic platforms.
  • Drive initiatives in data modelling, warehousing, and integration using tools like Microsoft Dataverse.
  • Design scalable, cloud-based data architectures utilising Azure, AWS, and advanced AI/big data services.
  • Build logical frameworks for data warehouses, data marts, and operational data stores.
  • Partner with cross-functional teams to align data architecture with strategic business goals.

Data Security and Governance

  • Create governance frameworks to ensure data quality, privacy, and regulatory compliance.
  • Define and enforce master data management strategies to maintain consistency across systems.
  • Implement policies for secure access, encryption, and data sharing.
  • Maintain detailed documentation of data architecture, lineage, and technical frameworks.

Performance Optimisation and Reporting

  • Enhance data architecture to improve performance, ensuring low latency and high throughput.
  • Establish and enforce enterprise standards for data architecture and integration.
  • Design dashboards, reports, and visualisations that meet organisational needs.
  • Collaborate with analysts to develop reporting systems that enable data-driven decision-making.

Leadership and Team Development

  • Lead and mentor the Business and Data Architecture team, fostering a collaborative and supportive work environment.
  • Define clear objectives, monitor progress, and manage team performance to ensure high-quality delivery.
  • Provide coaching and development opportunities for team members to reach their full potential.

Core Knowledge and Skills

  • In-depth expertise in data architecture design, including modelling and integration with Azure and AWS platforms.
  • Proficient in tools like Python, Power BI, SQL, and Azure Synapse Analytics.
  • Strong understanding of data privacy laws (e.g., GDPR) and governance best practices.
  • Advanced analytic and statistical skills, including hypothesis testing and scenario planning.
  • Exceptional stakeholder management and communication skills.

Experience and Qualifications

  • Demonstrated success in designing and implementing cloud-based data solutions.
  • Hands-on experience with AI, machine learning, and data analytic platforms.
  • 5+ years of leadership experience managing database and data quality engineering teams.
  • Certifications in platforms such as Azure Data Engineer are highly desirable.



Why Join?

My client offers a competitive salary of 68,500 along with an attractive benefits package, including:

  • Hybrid working: Only two days a week in the office.
  • A generous pension scheme to secure your future.
  • A great working environment, with a modern and inspiring office space.
  • A fantastic work culture that values collaboration, innovation, and professional growth.

This is a unique opportunity to contribute to meaningful projects that have a significant impact on organisational transformation. Youll have the chance to shape and lead innovative data strategies while working in a collaborative, future-focused environment.

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.