Senior ML Data Platform Engineer

WD; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

WD is building the infrastructure behind the AI-driven data economy in Singapore. You will develop ML-ready scientific data pipelines for experimental measurement data from precision instruments, enabling high-quality training data and reproducible ML workflows.

Collaborate across teams to ensure data contracts and governance are in place while expanding real-time ingestion capabilities. The role emphasizes end-to-end pipeline engineering, data quality, and governance in a scalable environment

Qualifications

• Bachelor's or Master’s degree in AI, CS, Data Eng, Electrical Eng, Applied Math or related field; AI major preferred; strong fundamentals.
• 2–3 years of experience building end-to-end data pipelines; solid Python and SQL skills.
• Experience with pipeline design, data quality checks, and data governance concepts.

Responsibilities

• Build and maintain feature engineering pipelines transforming raw engineering/ sensor/ operational data into ML-ready feature sets.
• Design and operate data quality checks ensuring completeness, schema consistency, and distribution stability.
• Maintain training data versioning and lineage to ensure reproducibility of model training.
• Implement data contracts between upstream producers and downstream ML consumers with access control.
• Contribute to real-time sensor data ingestion pipelines; progressively take ownership over 6–12 months.
• Support synthetic data pipelines and integration with ML platform components.
• Develop MLOps data layer including training dataset registry and feature store.

Skills

Python

SQL

Pipeline design

Data quality

Data lineage

ML data lifecycle

Education

Bachelor's or Master's degree in AI/CS/Data Eng

Tools

Airflow

AWS Glue

Feast/Tecton

Job description

WD is building the infrastructure behind the AI-driven data economy in Singapore. You will develop ML-ready scientific data pipelines for experimental measurement data from precision instruments, enabling high-quality training data and reproducible ML workflows.

Collaborate across teams to ensure data contracts and governance are in place while expanding real-time ingestion capabilities. The role emphasizes end-to-end pipeline engineering, data quality, and governance in a scalable environment