At a Glance
- Tasks: Design and own scalable data solutions that transform regulatory compliance.
- Company: Join CUBE, a leading RegTech firm at the forefront of AI-driven solutions.
- Benefits: Competitive salary, remote work options, and opportunities for personal growth.
- Other info: Collaborate globally with diverse teams and drive innovation in regulatory compliance.
- Why this job: Make a real impact in a fast-paced environment with cutting-edge technology.
- Qualifications: 7+ years in data architecture or software engineering with strong SQL skills.
The predicted salary is between 70000 - 90000 £ per year.
CUBE are a global Reg Tech business defining and implementing the gold standard of regulatory intelligence for the financial services industry.
We deliver our services through intuitive Saa S solutions, powered by AI, to simplify the complex and everchanging world of compliance for our clients.
Why us?
CUBE is a globally recognized brand at the forefront of Regulatory Technology. Our industry-leading Saa S solutions are trusted by the world’s top financial institutions globally.
In 2024, we achieved over 50% growth, both organically and through two strategic acquisitions.
We’re a fast-paced, high-performing team that thrives on pushing boundaries—continuously evolving our products, services, and operations.
At CUBE, we don’t just keep up we stay ahead.
We believe our future is built by bold, ambitious individuals who are driven to make a real difference.
Our “make it happen” culture empowers you to take ownership of your career and accelerate your personal and professional development from day one.
With over 700 CUBERs across 19 countries spanning EMEA, the Americas, and APAC, we operate as one team with a shared mission to transform regulatory compliance.
Diversity, collaboration, and purpose are the heartbeat of our success.
We were among the first to harness the power of AI in regulatory intelligence, and we continue to lead with our cutting-edge technology.
At CUBE, You will work alongside some of the brightest minds in AI research and engineering in developing impactful solutions that are reshaping the world of regulatory compliance.
Role Mission
The Data Solution Architect defines and owns the design of scalable, secure, and high-performing data solutions that support customer and operational systems.
This role is responsible for setting architectural direction, ensuring alignment with business needs, and guiding teams to deliver robust, production-grade solutions.
The Data Solution Architect works across engineering, product, and data teams to ensure solutions are well-designed, maintainable, and aligned with standards for performance, security, and governance.
Key Responsibilities
- Design and own end-to-end data solution architectures that meet defined requirements for scalability, performance, security, and maintainability.
- Translate complex business and product requirements into clear architectural designs, ensuring alignment with enterprise standards and future scalability needs.
- Define and enforce technical standards for data architecture, including data modelling, integration patterns, and system design.
- Provide technical leadership and guidance to engineering teams, supporting implementation and ensuring adherence to architectural principles.
- Review and approve solution designs, code, and implementations to ensure quality, consistency, and alignment with standards.
- Ensure solutions meet defined performance and reliability benchmarks (e. g. system throughput, latency, fault tolerance).
- Lead the identification and resolution of complex technical issues, including performance bottlenecks and architectural limitations.
- Drive improvements in system design, scalability, and maintainability through proactive refactoring and architectural evolution.
- Define and support implementation of CI/CD, testing, and deployment strategies to ensure reliable and efficient delivery.
- Ensure all solutions adhere to security, privacy, and compliance requirements, including secure data handling practices.
- Maintain clear architectural documentation, including system designs, decision records, and operational guidance.
- Collaborate with cross-functional and global teams to align on architecture, standards, and delivery priorities.
Skills & Competencies
- Data Architecture & System Design – Strong experience designing scalable, distributed data systems, including data models, storage, and processing layers.
- SQL & Data Processing – Deep understanding of SQL and data querying, with ability to design efficient data structures and transformations.
- Data Integration & Pipelines (ETL/ELT) – Expertise in designing and optimising data pipelines (e. g. SSIS or equivalent tools and frameworks).
- Programming (e. g. Python) – Experience using Python or similar languages for data processing, automation, or pipeline development.
- Cloud & Platform Technologies – Familiarity with modern data platforms and cloud-based architectures (desirable).
- Performance & Scalability Optimisation – Ability to design and tune systems to meet performance, reliability, and scalability requirements.
- Security & Compliance – Strong understanding of secure system design, data protection, and regulatory requirements.
- Dev Ops & CI/CD – Experience implementing automated build, test, and deployment pipelines to support reliable delivery.
- Technical Leadership – Provides architectural guidance, reviews work, and supports teams in delivering high-quality solutions.
- Cross-Team Influence – Works across teams and regions to align on standards, resolve dependencies, and drive consistency.
- Required Experience & Qualifications
- Proven experience in a data architecture, software engineering, or technical leadership role (typically 7+ years).
- Strong experience designing and delivering scalable data solutions in production environments.
- Expertise in data modelling, system design, and integration patterns.
- Strong experience with SQL and data processing at scale.
- Experience working with data pipeline and ETL tools (e. g. SSIS or equivalent).
- Experience with programming languages (e. g. Python) for data processing or automation.
- Experience defining or contributing to technical standards and architecture frameworks.
- Proven ability to lead technical design and guide delivery across teams.
- Strong communication skills, including translating technical concepts for non-technical stakeholders
CUBE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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Data Solution Architect employer: Cube Asia
CUBE is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for professionals in customer analytics. With a commitment to employee growth, the company offers mentoring opportunities and encourages continuous improvement through advanced analytics projects. Located in a vibrant area, CUBE provides a supportive environment where diverse talents can thrive and contribute to meaningful insights that drive customer trust and business success.
StudySmarter Expert Advice🤫
We think this is how you could land Data Solution Architect
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Cube Asia!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Solution Architect at Cube Asia.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Cube Asia.
✨Apply Directly through Our Website
When you find a suitable opening like Data Solution Architect at Cube Asia, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Solution Architect
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Cube Asia, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Cube Asia. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Cube Asia
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Cube Asia!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
