Data Solution Architect NEW

Doist

CUBE are a global RegTech business defining and implementing the gold standard of regulatory intelligence for the financial services industry. We deliver our services through intuitive SaaS 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 SaaS 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.
• DevOps & 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.