Data and Platform Engineer

We are looking for a Data & Platform Engineer to join an Advanced Analytics team building a next-generation Data Science and AI platform. You will play a key role in designing and maintaining the data foundations that enable analytics, machine learning, and AI solutions across the organisation. This is a great opportunity for an engineer who enjoys building scalable data pipelines, enabling data teams, and contributing to a modern cloud-based data and AI ecosystem. What you will do Platform Engineering Build and maintain a modern Data Science & AI platform supporting ML experimentation, deployment, and monitoring. Implement MLOps practices and CI/CD pipelines for data and ML workloads. Design scalable and reliable infrastructure for data and AI solutions. Data Engineering Develop and optimize robust data ingestion pipelines with a focus on reliability, quality, and security. Build and maintain data models supporting analytics and advanced use cases. Collaborate with Data Scientists to operationalize features, datasets, and ML workflows. Collaboration & Enablement Work closely with Data Scientists, Analysts, and Architects to deliver reusable, high-quality data assets. Improve platform usability through documentation, automation, and continuous enhancements.

3+ years of experience in Data Engineering or Platform Engineering roles. Strong experience with cloud-based data analytics environments. Hands-on expertise with Databricks (Spark, Jobs, Workflows, Delta Lake). Solid experience with Infrastructure-as-Code (Terraform preferred). Strong programming skills in Python and PySpark. Good knowledge of SQL, Git, and CI/CD practices. Understanding of containerization concepts (Docker, Kubernetes is a plus). Experience with cloud platforms (Azure is a plus). Fluent in English. Availability to work on-site 2 days per week. What will make you successful Experience building or supporting Data Science / AI platforms. Strong problem-solving mindset and ability to work in collaborative, cross-functional teams. Ability to communicate clearly with both technical and non-technical stakeholders.