AI Data Engineer

About the role

The AI Data Engineer at Mex Digital is responsible for centralising customer data and constructing robust reporting datasets that form the foundation for data-driven business decisions. In this position, you will own the development of data-driven solutions specifically designed to support customer retention strategies and enhance lifetime value across the business. A critical part of the role involves exploring generative AI technologies to build innovative trader applications that simplify and personalise the trading experience for end users. You will act as the technical bridge between complex data systems and business objectives, ensuring that data flows seamlessly and is actionable for stakeholders. This role requires a strong commercial awareness to identify opportunities where technology can boost engagement or streamline internal workflows. Success in this position will be measured by the reliability of your data infrastructure and the impact of your solutions on key business metrics. You will work closely with cross-functional teams to translate business requirements into scalable data architectures.

Key facts

What you'll do

• Identify opportunities where technology can increase customer engagement or automate internal tasks while maintaining strong commercial awareness and alignment with business needs.
• Analyse complex datasets to uncover customer insights, communicating findings to diverse stakeholders and strategizing approaches to increase engagement and lifetime value.
• Build and maintain scalable data pipelines and automations using Python to connect first-party databases, marketing platforms, and other data collection endpoints.
• Deploy machine learning solutions end to end with Python, focusing on predictive modelling, customer segmentation, and reliable model deployment in production environments.
• Leverage strong SQL expertise to interrogate raw data and high-volume datasets such as customer journey, marketing performance, and product behaviour.
• Utilise ETL tools like dbt and AWS Glue, and operate within cloud environments including AWS and SageMaker to ensure stable and efficient data operations.
• Construct applications using LLMs to summarise high volumes of data, incorporating the latest generative AI use cases tailored for trader applications.
• Present complex data insights to non-technical stakeholders, translating technical results into clear strategic options that influence business strategy.
• Ensure data quality and integrity across systems, creating trustworthy datasets that support accurate reporting and decision-making.
• Collaborate closely with marketing teams and other stakeholders to ensure data solutions meet evolving business requirements.
• Design and implement data models that optimise for performance, scalability, and ease of use across the organisation.
• Monitor data pipeline health and performance, proactively identifying issues and implementing improvements to reduce downtime.
• Document data processes and methodologies thoroughly to support knowledge transfer and long-term maintainability.
• Stay current with advancements in generative AI and data engineering tools to continuously enhance the capabilities of the data team.
• Support ad-hoc analysis requests and provide rapid insights to assist leadership in making timely decisions.

Requirements

The role requires a bachelor's degree, though the specific field is to be confirmed You must demonstrate strong SQL expertise applied to raw data and high-volume datasets such as customer journey, marketing performance, or product behaviour. Proven experience creating pipelines and automations with Python connecting first party databases, marketing platforms, or other data collection platforms and multiple endpoints is essential. You should have hands-on experience deploying machine learning solutions end to end using Python, particularly in predictive modelling, customer segmentation, and model deployment. The ability to analyse data to extract customer insights and communicate these findings to different stakeholders is a critical requirement. Experience building applications using LLMs to summarise high volumes of data, with knowledge of the latest generative AI use cases for trader applications, is required. Familiarity with ETL tools such as dbt and AWS Glue, along with cloud environments like AWS and SageMaker, must be demonstrated with strong communication skills. You must be able to present complex data insights to non-technical stakeholders, translating technical results into strategic options for business strategy. A strong portfolio of past analyses is valued and may outweigh formal educational qualifications in hiring decisions.

Nice to have

Only items explicitly stated as preferred in the source are listed here, and no additional preferences are added.

Practical notes

This role operates from the Dubai Office on full-time terms and involves collaboration with marketing and other stakeholders. Typical interview steps include data interviews that commonly feature a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model, and some companies provide a take-home analysis. Expect questions regarding past projects and the business impact of your work, with interviewers evaluating how you communicate uncertainty and business impact, not only technical accuracy. Bringing a clean write-up of a past analysis to the interview is well received.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialise in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.

About the company

Mex Digital is hiring for AI Data Engineer. Dubai Office.