Driving Innovation and Trust: Ten’s Journey to Redefine Service Excellence
Ten is on a mission to become the most trusted service business in the world. Technology-driven Product is at the centre of our strategy to create a hugely successful service and business. Millions of members already have access to Ten's services across lifestyle, travel, dining and entertainment on behalf of over 50 clients including HSBC, Swisscard, Visa, Mastercard and American Express. Ten's partnerships are based on multi-year contracts generating revenue through platform-as-a-service and technology fees.
We have the advantages of already being at scale globally with a critical mass of high-net-worth members via stable, multi-year revenue-generating contracts. We already have a market leading consumer proposition and credibility (and many integrations) with the leading suppliers/partners across our ‘big 4’ service categories of restaurants/travel/entertainment and luxury retail.
We are debt-free, profitable and the first B Corp listed on the London Stock Exchange (AIM market).
Our plans are to continue to invest into technology (including AI) to become the main way that our members organise their leisure lives. The next few years will see Ten speed up our progress via our Growth Engine strategy making the next huge steps to achieve our ambitions together.
For more information about Ten, please check out our Welcome to Ten video and this article .
The role
We are looking for a Data Engineer to be responsible for building a robust, scalable, and high-quality data foundation that enables analytics, reporting, and product decision-making across the organisation.
In this role, you will design, implement, and maintain the end-to-end data infrastructure, from ingestion to modelling to delivery, ensuring that data is accurate, accessible, and optimised for business use. A core part of the role is partnering with cross-functional teams including Data Analysts, Engineering, and Client Services to translate business needs into technical solutions.
Key responsibilities
1. Data Quality, Governance & Documentation
• Establish and maintain data quality checks, validation processes, and governance standards.
• Ensure consistent documentation across data sources, pipelines, and models.
2. Data Pipeline Development & Modelling
• Build scalable pipelines that ingest, normalise, and transform data from multiple internal systems into a unified, central data store.
• Develop clean, well-structured data models ready for analysis and reporting.
3. Data Access & Delivery (APIs & Feeds)
• Build APIs and data delivery mechanisms that provide fast, reliable access to analytics, insights, and reports.
• Partner with Data Analysts to ensure data is easily consumable for reporting and decision-making.
• Develop ingestion APIs and solutions for importing external or client data into databases.
• Own and maintain Data Feeds, ensuring timely fixes and high reliability.
4. Performance & Database Optimisation
• Improve data accessibility, query performance, and database efficiency.
• Work closely with Engineering to align on best practices and architectural improvements.
5. Impact & Roadmap Support
• Model and analyse the impact of potential product or engineering roadmap items to support prioritisation and decision-making.
6. Scalable Infrastructure & DevOps
• Design and operate modern, scalable data infrastructure in AWS (or an equivalent cloud platform).
• Apply software engineering and DevOps best practices including CI/CD, infrastructure-as-code, monitoring, and automation.
7. Our Tech Stack
• SQL
• Python,
• AWS (Lambda, ECS),
• Airflow
• Snowflake
• MS SQL Server, PostgreSQL
• GitHub, Jira
What we need from you:
• Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or a related field.
• 5+ years’ experience building data pipelines using Python – strong hands-on coding experience is essential.
• Proven experience working with AWS, specifically Lambda and ECS.
• Strong knowledge and hands-on experience using Airflow for ETL/ELT data pipelines.
• Familiarity with frameworks and tools such as Spark and Pandas.
• Ability to work with both batch and, ideally, streaming data processing.
• Experience building APIs and data delivery solutions, with a strong focus on data cleansing, integration and quality.
• Extensive hands-on experience with SQL, including building transformations, validating data and optimising analytical workloads.
• Strong communication skills, with the ability to translate complex technical concepts into clear, actionable insights for business stakeholders.
Guidelines for Hybrid/Home Office:
• This role is Cape Town–based and requires candidates to commute to the office at least 2 days per week. Please note this is a non-negotiable requirement.
• A secure home office at your confirmed address, free from background noise or other distractions when working remotely
• You must meet our minimum internet speeds if you want to work in our hybrid model and this will be checked during the recruitment process and again when you join. We also have a great office that you can work from as an alternative.