Senior Data & AI Analyst

Job Description: Senior Data & AI Engineer

Location: Singapore

Employment Type: Full-Time, Permanent

About the Role

We are seeking an experienced Senior Data & AI Engineerto lead the build and operationalisation of a modern data platform across theAsia-Pacific region.

This is a hands-on engineering role suited for someone whoenjoys designing scalable data infrastructure, building production-gradepipelines, and enabling advanced analytics and AI capabilities across theorganisation.

You will take ownership of the data platform, ensuringrobust data pipelines, strong governance, and a high-quality foundation foranalytics and AI use cases.

Key Responsibilities

1. Data Platform Engineering

• Design, build, and optimise end-to-end data pipelines from multiple source systems (ERP, CRM, operational systems)
• Develop and maintain scalable data architectures (e.g. lakehouse, medallion architecture)
• Build and optimise pipelines using modern data engineering tools and frameworks
• Integrate data across cloud and on-premise environments
• Implement monitoring, alerting, and automated recovery for pipelines
• Establish standards, documentation, and best practices for data engineering

2. Data Quality & Governance

• Implement data validation, quality checks, and monitoring frameworks
• Establish data governance practices including lineage, ownership, and access control
• Define and enforce data standards and KPI consistency
• Ensure compliance with internal data policies and regional requirements

3. Analytics & Data Modelling

• Develop and maintain semantic data models for reporting and analytics
• Support dashboarding and reporting platforms through structured datasets
• Collaborate with business stakeholders to translate requirements into data models
• Standardise definitions and ensure consistency across reporting outputs

4. AI & Advanced Analytics Enablement

• Build and maintain a high-quality data foundation for AI and machine learning use cases
• Support integration of AI-driven features such as natural language query and analytics tools
• Collaborate with cross-functional teams on AI-related initiatives

5. Stakeholder & Project Management

• Act as the technical owner of the data platform
• Collaborate with internal teams, stakeholders, and external vendors
• Communicate progress, risks, and technical decisions clearly
• Mentor junior team members and promote best practices

Requirements

Experience

• 5–8 years of experience in data engineering, data platforms, or analytics engineering
• Proven experience building and maintaining data pipelines end-to-end
• Hands-on experience with modern data platforms (e.g. Azure, lakehouse architecture)
• Experience working with cross-functional or regional teams
• Experience managing vendors or implementation partners is a plus

Technical Skills

• Strong proficiency in Python (PySpark) and SQL
• Experience with:
• Data pipeline orchestration (ETL / ELT)
• Cloud data platforms (e.g. Azure Data Factory, Synapse, ADLS)
• Data modelling (star schema, medallion architecture)
• Experience with BI tools (e.g. Power BI) and semantic modelling
• Exposure to data governance tools and frameworks
• Familiarity with version control (e.g. Git)
• Understanding of AI/ML concepts and data integration

Education

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field

Key Competencies

• Strong problem-solving and engineering mindset
• High attention to detail and data quality
• Ability to work independently in a fast-paced environment
• Strong communication skills across technical and non-technical stakeholders
• Proactive, collaborative, and solutions-driven