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

Apply Now

Solution Architect

NTT DATA
London
8 months ago
Applications closed

Related Jobs

View all jobs

Data Architect

Data Architect

Data Architect

Data Architect

Data Architect

Data Architect - Azure

Job Description

What you'll be doing:

You will be working for the Lead Solution Architect in a Solution Architect role for TMDC across multiple different components, mostly based around Java tooling (both OLTP and Batch) but also including Python aspects. The components run on the banks on-premises infrastructure and on the banks GCP installation. 

Carrying out Architecture and design work to propose/refine technical implementation options Working closely with Business Analysts to understand functional and non-functional requirements to feed into your Architecture/Design work Define and maintain interface definitions across our internal components and for our external interfaces Working closely with SRE team to understand their needs and define solution improvements to accommodate these Working closely with our QA team to help decision making on what testing to carry out and how to integrate to solutions Taking responsibility for the completeness of Architecture records and documentation Running the Architecture forum for the TMDC domain Working across multiple squads to assist Tech Leads and Senior Engineers with design and compliance activities

What experience you'll bring:

Experienced Software Engineer, including extended experience with Java Combined experience as a Software Engineer then Solution Architect Deep professional experience of at least one storage technology, preferably Oracle or Google Big Query Professional experience working with Google Cloud Platform Professional experience of at least one "CI/CD" tool such as Team City, Jenkins, GitHub Actions Experience of working with Agile build and deployment practices Knowledge and track record of creating and delivering technical designs that consider the full range of non-functional requirement categories (e.g. reliability, scalability, observability, testability) Deep understanding of relevant Architecture styles and their trade-offs - e.g. Microservices, Monolith, Batch Experience of working in one of more large data integration projects/products Experience of working with a globally distributed team requiring remote interaction across locations, time zones and diverse cultures Data modelling experience Understanding of data security principles and implementation considerations Excellent communication skills (verbal and written)

Ideal to Have

Knowledge of DB environment (e.g. DB GCP, Fabric, DWEB, eIDp, AutoBahn) Previous experience of working in a role requiring significant Data Architecture contribution Experience and knowledge of Data Engineering topics such as partitioning, optimisation based on different goals (e.g. retrieval performance vs performance) Experience working with confidential data and strategies to avoid direct use of raw data Experience related to any of payment scanning, fraud checking, integrity monitoring, payment lifecycle management Experience working with TMDC GCP tech stack – Cloud Composer, Dataproc, BigQuery, Looker Experience working with Apache Spark Experience working with Kotlin Experience working with Drools or similar product (e.g. Red Hat rules, IBM ODM, Open Rules) Experience of different JavaScript frameworks (e.g. React, Angular)

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

what we'll offer you:

We offer a range of tailored benefits that support your physical, emotional, and financial wellbeing. Our Learning and Development team ensure that there are continuous growth and development opportunities for our people. We also offer the opportunity to have flexible work options.

You can find more information about NTT DATA UK & Ireland here: NTT DATA UK & I 

We are an equal opportunities employer. We believe in the fair treatment of all our employees and commit to promoting equity and diversity in our employment practices. We are also a Disability Confident Committed Employer - we want to see every candidate performing at their best throughout the job application and interview process, if you require any reasonable adjustments during the recruitment process, please let us know and we look forward to hearing from you.

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

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.

Jobs

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.

Jobs

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.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.