Design and optimise scalable data workflows with subject matter expertise in data loading patterns, data architecture etc.
Develop and maintain robust data pipelines that support both real-time and batch processing
Extract and integrate data from various sources, developing and scaling models in real-time business conditions. This includes interfacing (via API) between the data layer and application layer.
Leverage on SQL to ensure efficient data transformation and analytics
Implement data modelling best practices to support AI/ML applications, including schema design, partitioning strategies and indexing for performance optimisation
Integrate diverse data sources (e.g. structured, semi-structured and unstructured) into unified data architectures that power AI-driven applications and insights
Train advanced models and algorithms suitable for business use Models include computer vision models, forecasting models, route optimisation etc.
Work as a team to ensure data readiness, feature engineering pipelines and reproducibility of experiments
Champion data quality and governance by implementing validation, lineage tracking, and compliance standards
Serve as data engineer, software engineer, cloud engineer and AI scientist all-in-one
Job Requirements
At least Bachelor Degree in Engineering, Economics, Mathematics, Computer Science or related areas
Minimum 5-8 years of work experience in a related role dealing with artificial intelligence
Advanced understanding in software engineering practices (e.g. Version Control), containerization, CI/CD pipelines
Experience with deploying models using frameworks like TensorFlow, PyTorch, and extremely familiar with platforms like Azure, Databricks, Fabric
Advanced proficiency in SPARK, Python, Java, SQL, Pandas, Hugging Face, Open AI APIs
Familiarity with data manipulation, statistical analysis and machine learning theories. This includes extracting and integration of data from various sources, developing and scaling models in real-time business conditions. This includes interfacing (via API) between the data layer and application layer.
Advanced proficiency with both full stack software engineering and data engineering with solid experience with working with Azure etc.
Familiar with data ethics and governance including best practices on how data should be managed securely
