Data Solution Architect

NTT DATA
London
3 months ago
Applications closed

Related Jobs

View all jobs

Data & AI Solution Architect

Data & AI Solution Architect

Solution Architect

Pre-Sales AI Solution Designer

Enterprise Data Governance & Architecture Lead

Data & AI Architect, Microsoft Azure, PaaS, ETL, Data Modelling Remote

Job Description

What you'll be doing:

NTT DATA are looking for a Lead Data Solutions Architect to work within a dynamic, remote-first data architectural capability to deliver cloud based data solutions using best-in-class RDBMS, ETL/ELT, and Cloud platforms for blue-chip customers across a range of sectors.

You will lead cross-functional teams of Data Engineers, Architects, Business Analysts and Quality Assurance Analysts to provision data processing, storage, and visualisation capabilities in an Agile environment. You will be comfortable with stakeholder engagement and take overall ownership of the technical delivery of your team and the solution they are building.

What experience you'll bring:

Experience and Leadership:Proven experience in data architecture, with a recent role as a Lead Data Solutions Architect, or a similar senior position in the field. Proven experience in leading architectural design and strategy for complex data solutions and then overseeing their delivery. Experience in consulting roles, delivering custom data architecture solutions across various industries.Architectural Expertise:Strong expertise in designing and overseeing delivery of data streaming and event-driven architectures, with a focus on Kafka and Confluent platforms. In-depth knowledge in architecting and implementing data lakes and lakehouse platforms, including experience with Databricks and Unity Catalog. Proficiency in conceptualising and applying Data Mesh and Data Fabric architectural patterns. Experience in developing data product strategies, with a strong inclination towards a product-led approach in data solution architecture. Extensive familiarity with cloud data architecture on platforms such as AWS, Azure, GCP, and Snowflake. Understanding of cloud platform infrastructure and its impact on data architecture.Data Technology Skills:A solid understanding of big data technologies such as Apache Spark, and knowledge of Hadoop ecosystems. Knowledge of programming languages such as Python, R, or Java is beneficial. Exposure to ETL/ ELT processes, SQL, NoSQL databases is a nice-to-have, providing a well-rounded background. Experience with data visualization tools and DevOps principles/tools is advantageous. Familiarity with machine learning and AI concepts, particularly in how they integrate into data architectures.Design and Lifecycle Management:Proven background in designing modern, scalable, and robust data architectures. Comprehensive grasp of the data architecture lifecycle, from concept to deployment and consumption.Data Management and Governance:Strong knowledge of data management principles and best practices, including data governance frameworks. Experience with data security and compliance regulations (GDPR, CCPA, HIPAA, etc.)Leadership and Communication:Exceptional leadership skills to manage and guide a team of architects and technical experts. Excellent communication and interpersonal skills, with a proven ability to influence architectural decisions with clients and guide best practicesProject and Stakeholder Management:Experience with agile methodologies (e.g. SAFe, Scrum, Kanban) in the context of architectural projects. Ability to manage project budgets, timelines, and resources, maintaining focus on architectural deliverables.

Who we are:

We’re a business with a global reach that empowers local teams, and we undertake hugely exciting work that is genuinely changing the world. Our advanced portfolio of consulting, applications, business process, cloud, and infrastructure services will allow you to achieve great things by working with brilliant colleagues, and clients, on exciting projects.

Our inclusive work environment prioritises mutual respect, accountability, and continuous learning for all our people. This approach fosters collaboration, well-being, growth, and agility, leading to a more diverse, innovative, and competitive organisation. We are also proud to share that we have a range of Inclusion Networks such as: the Women’s Business Network, Cultural and Ethnicity Network, LGBTQ+ & Allies Network, Neurodiversity Network and the Parent Network.

For more information on Diversity, Equity and Inclusion please click here: Creating Inclusion Together at NTT DATA UK | NTT DATA

Back to search Email to a friend Apply now

Apply

Listen to the story of Employee Voice

Alejandro Hernandez

Agile Coach/Digital Strategy Consultant for the Banking Sector

Chile

Read more

Giuseppe Cuciniello

International Business Development and commercial planning

Italy

Read more

Ianca Caroline Nascimento Linhares

Agility Trainee

Brazil

Read more

Apply Back to search results

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.

10 Ways AI Pros Stay Inspired: Boost Creativity with Side Projects, Hackathons & More

In the rapidly evolving world of Artificial Intelligence (AI), creativity and innovation are critical. AI professionals—whether data scientists, machine learning engineers, or research scientists—must constantly rejuvenate their thinking to solve complex challenges. But how exactly do these experts stay energised and creative in their work? The answer often lies in a combination of strategic habits, side projects, hackathons, Kaggle competitions, reading the latest research, and consciously stepping out of comfort zones. This article will explore why these activities are so valuable, as well as provide actionable tips for anyone looking to spark new ideas and enrich their AI career. Below, we’ll delve into tried-and-tested strategies that AI pros employ to drive innovation, foster creativity, and maintain an inspired outlook in an industry that can be both exhilarating and daunting. Whether you’re just starting your AI journey or you’re an experienced professional aiming to sharpen your skills, these insights will help you break out of ruts, discover fresh perspectives, and bring your boldest ideas to life.

Top 10 AI Career Myths Debunked: Key Facts for Aspiring Professionals

Artificial Intelligence (AI) is one of the most dynamic and rapidly growing sectors in technology today. The lure of AI-related roles continues to draw a diverse range of job seekers—from seasoned software engineers to recent graduates in fields such as mathematics, physics, or data science. Yet, despite AI’s growing prominence and accessibility, there remains a dizzying array of myths surrounding careers in this field. From ideas about requiring near-superhuman technical prowess to assumptions that machines themselves will replace these jobs, the stories we hear sometimes do more harm than good. In reality, the AI job market offers far more opportunities than the alarmist headlines and misconceptions might suggest. Here at ArtificialIntelligenceJobs.co.uk, we witness firsthand the myriad roles, backgrounds, and success stories that drive the industry forward. In this blog post, we aim to separate fact from fiction—taking the most pervasive myths about AI careers and debunking them with clear, evidence-based insights. Whether you are an established professional considering a career pivot into data science, or a student uncertain about whether AI is the right path, this article will help you gain a realistic perspective on what AI careers entail. Let’s uncover the truth behind the most common myths and discover the actual opportunities and realities you can expect in this vibrant sector.

Global vs. Local: Comparing the UK AI Job Market to International Landscapes

How to navigate salaries, opportunities, and work culture in AI across the UK, the US, Europe, and Asia Artificial Intelligence (AI) has evolved from a niche field of research to an integral component of modern industries—powering everything from chatbots and driverless cars to sophisticated data analytics in finance and healthcare. The job market for AI professionals is consequently booming, with thousands of new positions posted each month worldwide. In this blog post, we will explore how the UK’s AI job market compares to that of the United States, Europe, and Asia, delving into differences in job demand, salaries, and workplace culture. Additionally, we will provide insights for candidates considering remote or international opportunities. Whether you are a freshly qualified graduate in data science, an experienced machine learning engineer, or a professional from a parallel domain looking to transition into AI, understanding the global vs. local landscape can help you make an informed decision about your career trajectory. As the demand for artificial intelligence skills grows—and borders become more porous with hybrid and remote work—the possibilities for ambitious job-seekers are expanding exponentially. This article will offer a comprehensive look at the various regional markets, exploring how the UK fares in comparison to other major AI hubs. We’ll also suggest factors to consider when choosing where in the world to work, whether physically or remotely. By the end, you’ll have a clearer picture of the AI employment landscape, and you’ll be better prepared to carve out your own path.