Principal Data Engineer​/Data Architect

About Red Cloud

The global supply chain is broken - creating a $2 trillion inventory gap where essential consumer goods fail to reach the people who need them. Brands miss sales, distributors mismanage stock, and retailers face empty shelves. The result? Higher prices, slower growth, and lost opportunity across the board.

Red Cloud is fixing this. Our RedAI digital trading platform, bulk and retail trading exchanges connect key parts of the supply chain - enabling bulk inventory exchange, streamlined digital payments, and generating vast quantities of aggregated market data. By applying AI and machine learning techniques, we deliver predictive market insight and trading recommendations straight back to the trading environment - facilitating smarter everyday business decisions for our customers, from factory to warehouse to store.

Headquartered in London, Red Cloud became a publicly listed company on Nasdaq (RCT) in March 2025. With a diverse team spanning many nationalities and operations across Africa, the Middle East, Europe, and Latin America, we’re building a more connected and efficient global trade network. Our AI labs are busy exploring the next generation of smart AI agents and deeper FMCG market intelligence for the benefit of our customers across a growing operational footprint.

A Principal Data Engineer is responsible for designing, building, and maintaining the company’s data warehouse, ensuring data is accessible, performant, and easy to use across the business. This role sits at the core of enabling data-driven decision-making and AI initiatives.

You will work within a cross-functional squad alongside data scientists and AI engineers, contributing to the full lifecycle of how data is ingested, transformed, and consumed.

• Design and own the architecture and data flow into the data warehouse
  • Collaborate with product managers, engineers, and stakeholders
  • Ensure the platform is performing, scalable, secure, and readable and easy to use
  • Support business-wide data needs and use cases
  • Design, build, and maintain ELT pipelines
  • Integrate data from internal systems and external partners
  • Ensure data quality and accuracy, performance and scalability, and secure data handling
  • Deliver reliable, up-to-date datasets
  • Develop datasets and data products for internal and external customers
  • Ensure solutions meet or exceed requirements, are well documented and understandable, and validated for accuracy and performance
  • Enable data as a product capabilities
  • Conduct code and design reviews
  • Ensure adherence to best practices in scalability, readability, and security
  • Provide constructive, actionable feedback

• SQL & Database Design (Snowflake, Postgre
  
  SQL, MySQL)
• Python
• Data Warehousing Architecture
• ELT/ETL Pipelines
• Data Modelling

• Mentor engineers at all levels
• Support onboarding and development of new team members
• Conduct knowledge sharing and pair programming
• Business value delivered through data
• Incident response and resolution time
• Stability and uptime of data systems
• Mentorship effectiveness
• Participation in reviews, planning, and collaboration
• Enable data-driven decision-making across the company
• Power AI and analytics initiatives
• Improve customer value through data products
• Support revenue growth via data insights

• 25 days annual leave, increasing to 26 days after 12 months in the business
• Enhanced company pension (matched up to 5% & salary sacrifice)
• Healthcare cashplan with Medicash
• Private healthcare with Aviva
• Life insurance with AIG
• Happl, our benefit platform providing access to pre-negotiated discounts on a wide variety of services including entertainment, food, and fitness
• Stock / equity