Principal Engineer (AI & Data Engineering)

PERSOL; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

A leading technology company in Singapore seeks a Principal Engineer (AI & Data Engineering) to architect and manage a next-generation AI data platform. The ideal candidate will have extensive experience in data strategy, project management, and cloud platforms such as AWS and Azure. This senior leadership position calls for innovative thinkers who can guide engineering teams and ensure robust data governance and compliance.

Qualifications

• Minimum 8 years of relevant working experience, including 3 years in a leadership position.
• Proven ability to design and implement end-to-end data system solutions.
• Experience with cloud providers and data modelling techniques.

Responsibilities

• Develop and implement data strategy and architecture.
• Design, build, and manage efficient data pipelines.
• Oversee integration and governance of data for quality assurance.
• Ensure compliance with data security regulations.
• Mentor and guide engineering teams in best practices.

Skills

Data Strategy Development

Data Pipeline Management

Data Quality Assurance

Project Management

Communication Skills

Team Collaboration

Education

Tertiary qualification in Computer Science, Information Technology, or related discipline

Tools

AWS

Azure

GCP

SQL

Python

Snowflake

Databricks

Apache Spark

Job description

Lead the Architecture of our Next-Generation AI Data Platform

Are you a visionary data leader passionate about building robust, scalable data platforms that power mission-critical AI solutions? We are seeking a highly motivated Principal Engineer (AI & Data Engineering) to play a pivotal role in shaping the future of our data infrastructure.

In this senior leadership position, you will be the cornerstone of our AI Data Platform & Engineering function. You will be responsible for architecting, building, and governing the integrated data ecosystem that enables advanced analytics and artificial intelligence across the organization.

Key Responsibilities

• Architect the Data Strategy: Develop and implement a cohesive data strategy and architecture, aligning technology with business objectives and formulating the long-term capabilities roadmap for AI and Data Engineering.
• Build Scalable Data Systems: Design, build, and manage efficient, reliable data pipelines to process large volumes of data, optimizing performance for complex AI models.
• Ensure Data Integrity: Oversee the integration of data from diverse sources, establishing robust protocols for data quality, validation, and governance to ensure consistency, accuracy, and reliability.
• Uphold Security & Compliance: Ensure data security and full compliance with all relevant regulations and standards, including reviewing systems against enterprise governance and IM requirements.
• Drive Innovation & Leadership: Stay at the forefront of AI Data Engineering technologies and best practices. Guide and mentor a talented engineering team to deliver platforms and capabilities within stipulated timelines and scope.
• Foster Collaboration: Work closely with AI Product teams, Data Scientists, and business stakeholders to facilitate data sharing, design consumption models, and ensure the platform meets evolving needs.

Job Requirements

• Tertiary qualification in Computer Science, Information Technology, or a related discipline.
• Minimum of 8 years of relevant working experience, including at least 3 years in a leadership position overseeing data architecture and engineering.
• Strong planning and project management skills (PMP or equivalent certification is an advantage).
• Excellent interpersonal, communication, and facilitation skills for engaging a wide range of stakeholders.
• A proactive, independent worker who also excels within a team environment.
• Experience in building systems that comply with government IT policies (e.g., IM8) would be a significant advantage.

Core Expertise

• Proven ability to design and implement end-to-end data system solutions.

Cloud & Platforms

• A hands‑on experience with cloud providers (AWS, Azure, GCP) and platforms like Snowflake, Databricks, GCP BigQuery, or Azure Synapse.
• Strong knowledge in data modelling (OLTP, OLAP, Dimensional Modelling).
• Proficiency with ETL/ELT frameworks and tools (e.g., Airflow, dbt, Talend, Informatica).
• Experience with Big Data technologies (e.g., Spark, Kafka, Flink).

Programming

• A hands‑on experience with SQL, Python, and distributed systems.

Advantageous Skills

• Familiarity with the Hadoop ecosystem.
• Strong knowledge of networking and system security.