Data Science Engineer

• Designing and building scalable, reusable data pipelines using Azure Databricks, Data Factory, and modern cloud tooling
• Developing secure, flexible data models and optimising performance across massive datasets
• Collaborating with data scientists to productionise AI models and accelerate experimentation
• Integrating diverse data sources through automated ingestion frameworks
• Driving CI/CD, version control, and testing best practices across data workflows
• Exploring AI-driven automation to enhance data accuracy, efficiency, and decision-making
• Constantly improving data architecture and processes to support innovation at scale

• Strong hands-on experience with Azure Databricks, Data Factory, Blob Storage, and Delta Lake
• Proficiency in Python, PySpark, and SQL
• Deep understanding of ETL/ELT, CDC, streaming data, and lakehouse architecture
• Proven ability to optimise data systems for performance, scalability, and cost-efficiency
• A proactive problem-solver with great communication skills and a passion for AI-driven data engineering

Amtis is proud to partner with an advanced, data-driven organisation - a business that's not just talking about AI, but actively building intelligent systems powered by Azure, Databricks, and real-world machine learning applications. This is a hands-on engineering role where you'll be at the core of designing, developing, and optimising modern data platforms that enable predictive analytics, AI experimentation, and large-scale automation. You'll work in an environment where data truly drives business decisions - not just dashboards. If you're excited by high-volume, high-velocity data challenges and want to work on next-gen infrastructure that supports advanced analytics and AI workloads, this is your opportunity.