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.
Purpose of the job:
Lead the design, delivery, and operation of CUBE's modern data platform—the foundational infrastructure that transforms unstructured regulatory content into organised, governed, and AI-ready data assets.
Your mission is to build and scale a high-performing Azure-based data platform that enables complex analytical queries, powers AI-driven intelligence, and supports CUBE's position as the leading regulatory risk management platform. You will own the technical vision, roadmap, and delivery of data engineering capabilities that underpin our product innovation and customer value.
You will build, develop, and lead a multidisciplinary team of data engineers, data architects, and infrastructure engineers, fostering a culture of technical excellence, collaboration, and continuous improvement. This role is critical to CUBE's data and AI strategy.
Responsibilities:
Establish and enforce data governance frameworks, ensuring data quality, lineage, security, and compliance across the platform.
Build platform capabilities to support complex analytical queries, AI model training, and real-time intelligence requirements.
Collaborate with Data & AI Engineering leadership, product teams, and architects to align platform capabilities with business objectives and product requirements.
Drive technical delivery through agile practices, setting clear objectives, managing backlogs, and ensuring on-time, high-quality releases.
Champion engineering best practices including CI/CD, infrastructure as code, automated testing, and observability.
Optimise platform performance, cost efficiency, and reliability, monitoring key metrics and driving continuous improvement.
Build, develop, and mentor a high-performing team of data engineers, data architects, and infrastructure engineers.
Establish clear career frameworks, foster technical growth, and create an inclusive, collaborative team culture.
Stay abreast of emerging technologies and Azure platform capabilities, evaluating and adopting innovations that deliver competitive advantage.
Contribute to the broader Data & AI Engineering strategy and organisational initiatives.
What we’re looking for:
Significant experience as a Head of Data Engineering, Lead Data Platform Engineer, or equivalent senior technical leadership role.
Proven track record of designing and delivering modern data platforms at scale in B2B SaaS or enterprise environments.
Deep expertise in Microsoft Azure data services including Azure Data Factory, Synapse Analytics, Data Lake Storage, and Fabric.
Strong understanding of data architecture patterns for ingesting, transforming, and governing unstructured and semi-structured data.
Experience building data platforms that support AI/ML workloads, including feature engineering, model training pipelines, and inference infrastructure.
Hands-on knowledge of data governance frameworks, including data quality, lineage, cataloguing, and compliance requirements.
Proficiency in modern data engineering tools and practices including Python, SQL, Spark, Terraform, and CI/CD pipelines.
Experience leading and developing engineering teams, with demonstrated ability to recruit, mentor, and build high-performing technical organisations.
Strong understanding of agile delivery practices, backlog management, and technical project execution.
Excellent communication skills to articulate complex technical concepts to non-technical stakeholders and influence executive decision-making.
Mindset & Approach:
Strategic thinker with a pragmatic approach to technical delivery and trade-offs.
Engineering excellence mindset: passionate about quality, performance, and maintainability.
Outcome-driven and data-informed, measuring success through platform adoption, performance metrics, and business impact.
Strong people leadership capabilities with a focus on building inclusive, collaborative teams.
Growth-oriented: committed to continuous learning and developing team capabilities.
Comfortable navigating ambiguity and complexity, bringing clarity and focus for technical teams.
Commercial awareness, understanding how technical decisions align with business objectives and customer value.
Ownership-driven with accountability for technical delivery and platform reliability.
Interested?
If you are passionate about leveraging technology to transform regulatory compliance and meet the qualifications outlined above, we invite you to apply. Please submit your resume detailing your relevant experience and interest in CUBE.
CUBE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Top Skills
CUBE (cube.global) London, England Office
Tower 42, 25 Old Broad Street, London, United Kingdom, EC2N 1HN


