Strategic Enterprise Data Architect Lead

Datatech Analytics
London
6 days ago
Create job alert

Strategic Enterprise Data Architect Lead

Read the overview of this opportunity to understand what skills, including and relevant soft skills and software package proficiencies, are required.

Hybrid - Flexible on a variety of office UK locations - estimated 2 days in office

£Competitive Salary Neg DoE plus car allowance and good bonus potential

Full time/permanent

No sponsorship possible for this role and the ability to gain Security Clearance essential

Job Reference J12926

Our Global client's Data and Analytics Group leads on best practice use of data and builds strategic technical capability for the business. In this fantastic opportunity as Enterprise Data Architect, you'll shape and drive the data architecture strategy, creating, maintaining and promoting the data architecture strategy and roadmap. Including:

Developing, maintaining and communicating the Enterprise Data Architecture Strategy, together with the reference architecture and roadmaps for progression towards target stateEngaging with and influencing senior stakeholders to drive effective and coherent data-led operations across the companyCollaborating across Enterprise Architecture to ensure coherent strategy and delivery of solutions required to allow the business to meet its strategic and tactical goalsManaging the Head Office data architecture team and leading the data architecture community across the CompanySupporting data architecture implementation, assurance and compliance across the organisation, collaborating with a diverse range of stakeholders across the organisationAuthority and accountability for actions and decisions for data architecture, including technical and quality aspectsCollaborating with internal and external partners to facilitate effective evaluation of solutions to business needs, and working proactively and independently to articulate issues/challenges and support resolution

Your skills and experience:

Proven experience in data/information architecture or equivalent roles at Enterprise level essentialFamiliarity with industry-standard system integration and data modelling patterns, and frameworks such as ITIL, DAMA/DMBOK and TOGAF and familiarity with metadata management practicesExperience with cloud technologies (Azure and/or AWS), including multi-cloud and hybrid architecturesExperience of working in a multi-region highly regulated industryExperience of leading through change, in a matrix/hub-and-spoke model, without direct line management controlConfident with your communications and proven stakeholder, and man management experience.

This is a place where you'll be able to make a real difference. You'll be part of an inclusive culture that values diversity, rewards integrity, and merit, and where you'll be empowered to fulfil your potential.#J-18808-Ljbffr

Related Jobs

View all jobs

Strategic Enterprise Data Architect Lead

Lead Enterprise Data Architect

Azure Enterprise Data Architect | London | Insurance

Azure Enterprise Data Architect | London | Insurance

Enterprise Data Architect

SAP Data Lead

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 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.