Data Engineer – Customer Intelligence & AI Insights

Singapore Telecommunications Limited; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Singtel is hiring a data professional to design and maintain data pipelines and dashboards that reveal insights on service quality and customer journeys. You will apply statistical analysis and AI to detect patterns and predict issues to improve customer experience and platform reliability.

You will partner with Product, Engineering and Operations to translate data findings into measurable improvements, while ensuring data governance and scalable reporting across stakeholders.

Qualifications

• Degree in data-related field is required or strongly preferred.
• Strong hands-on SQL and at least one data-analysis language (Python) are essential.
• Experience building data pipelines from multiple sources and handling structured data.

Responsibilities

• Design, build and maintain data pipelines integrating customer behaviour, performance, and telemetry from multiple sources.
• Develop dashboards and analytics views to provide insights on service quality and customer journeys.
• Apply AI/ML techniques to identify patterns and predict issues for proactive management.
• Correlate technical performance with customer experience to guide improvements.
• Partner with product, engineering and operations to translate data insights into action.
• Define metrics for customer experience, video quality and application performance.

Skills

SQL

Python

Data pipelines

Data analytics

Communication

Education

Degree in Data Science, Computer Science, IT, Engineering, Statistics or related field

Tools

Power BI

Tableau

Job description

Singtel is hiring a data professional to design and maintain data pipelines and dashboards that reveal insights on service quality and customer journeys. You will apply statistical analysis and AI to detect patterns and predict issues to improve customer experience and platform reliability.

You will partner with Product, Engineering and Operations to translate data findings into measurable improvements, while ensuring data governance and scalable reporting across stakeholders.