Analytics Engineer

Location: Singapore (Mostly remote, sometimes in person)
Employment Type: Contract / Project-Based (with potential extension)

About the Opportunity

We are looking for an experienced Analytics Engineer to join a high-impact AI and data transformation project supporting a leading enterprise in Singapore.

You will play a key role in designing and building trusted analytics models that power AI-driven insights and business decision-making. Working alongside data engineers, AI engineers and business stakeholders, you will transform complex business requirements into scalable semantic models and reliable metrics.

This is an excellent opportunity for someone who enjoys solving business problems through data, has strong SQL expertise, and thrives in a collaborative, hands-on environment.

Key Responsibilities

• Design and develop semantic data models that support analytics and AI applications.

• Translate business requirements into trusted metrics, KPIs and reporting models.

• Build and maintain scalable data models within a cloud data warehouse environment.

• Collaborate with business stakeholders to define consistent business logic and data definitions.

• Optimise SQL queries and data models for performance, scalability and maintainability.

• Work closely with data engineers to ensure high-quality, reliable datasets.

• Support AI applications by providing well-structured and governed analytical data.

• Document data models, business rules and metric definitions.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering or a related discipline.

• At least 5 years of experience in Analytics Engineering, Data Analytics, Business Intelligence or Data Warehousing.

• Strong SQL skills with experience building production-grade analytical models.

• Experience with cloud data warehouse platforms such as Snowflake, Azure Synapse, BigQuery or Redshift.

• Strong understanding of dimensional modelling, star schemas and data warehouse design principles.

• Experience working with business stakeholders to define metrics and reporting requirements.

• Familiarity with modern data transformation tools such as dbt is an advantage.

• Exposure to AI or Generative AI projects is beneficial but not mandatory.

• Excellent analytical, communication and stakeholder management skills.

Preferred Skills

• Snowflake experience.

• dbt or similar data transformation frameworks.

• Experience supporting AI, machine learning or Retrieval-Augmented Generation (RAG) initiatives.

• Knowledge of data governance and data quality best practices.

• Experience working in Agile delivery environments.

Why Join?

• Work on an enterprise-scale AI and analytics transformation programme.

• Collaborate with a highly experienced cross-functional engineering team.

• Opportunity to influence modern data architecture and AI-enabled business solutions.

• Flexible hybrid working arrangement.

• Initial project engagement with potential for extension based on project needs.