Data Engineer

ST LOGISTICS PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

ST LOGISTICS PTE. LTD. seeks a data engineer to design and optimise scalable data workflows for AI-ready analytics.

You will build real-time and batch pipelines, extract and integrate data from diverse sources, and design data models to support AI/ML applications. The role interfaces between data and application layers via APIs and requires strong SQL, Python, Spark and cloud platform experience. The position emphasizes data quality, governance, and reproducibility, with cross-team collaboration

Qualifications

• Bachelor degree in a relevant field is required.
• Minimum 5 years of work experience in AI-related data engineering.
• Advanced understanding of software engineering practices, version control, containerization, and CI/CD pipelines.
• Experience deploying models with TensorFlow or PyTorch; familiar with Azure, Databricks and Fabric.

Responsibilities

• Design and optimise scalable data workflows with expertise in data loading patterns, data architecture.
• Develop and maintain robust data pipelines for real-time and batch processing.
• Extract/integrate data from multiple sources; interface via API between data and application layers.
• Leverage SQL for efficient data transformation and analytics.
• Apply data modelling best practices to support AI/ML applications and indexing for performance.
• Integrate diverse data sources into unified architectures powering AI-driven insights.
• Train advanced models; explore computer vision, forecasting, and route optimisation.
• Collaborate to ensure data readiness, feature engineering pipelines and reproducibility.
• Champion data quality and governance with validation, lineage tracking, and compliance.

Skills

Spark

Python

Java

SQL

Pandas

HuggingFace

OpenAI APIs

Version Control

Containerization

CI/CD

TensorFlow

PyTorch

Education

Bachelor Degree in Engineering, Economics, Mathematics, Computer Science or related areas

Tools

Azure

Databricks

Fabric

Job description

Job Responsibilities

• 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 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 withbothfull 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