AVP/VP, Data Platform Engineer, AI Alpha Group

GIC Private Limited; Singapore; Hybrid; SGD 80,000 - 120,000; Full time

Job summary

A leading global investment firm in Singapore is seeking a Data Platform Engineer to design and manage data foundations for AI-driven systems. You will collaborate with a cross-functional team to build optimized data pipelines and ensure data quality. Candidates should have at least 8 years of experience in data engineering, proficiency in Python and SQL, and a strong understanding of data architecture. This role offers a flexible work environment and the opportunity to make a significant impact.

Benefits

Flexible work arrangement

Professional growth opportunities

Qualifications

• 8+ years of experience in data engineering or platform engineering.
• Experience in AI or analytics-intensive environments.
• Strong coordination and communication skills.

Responsibilities

• Design and maintain scalable data pipelines.
• Build and optimize data ingestion workflows.
• Ensure data quality checks and governance practices.

Skills

Python

SQL

Data Architecture

Data Engineering

Feature Engineering

Cloud Environments

Data Modeling

Containerization (Docker, Kubernetes)

Web Scraping

Education

Bachelor's degree in Computer Science

Tools

PostgreSQL

Spark

Airflow

DuckDB

Kafka

ClickHouse

Job description

Overview

GIC is one of the world’s largest sovereign wealth funds. With over 2,000 employees across 11 offices around the world, we invest in more than 40 countries globally across asset classes and businesses. As a leading global long-term investor, we work at the Point of Impact for Singapore’s financial future, and the communities we invest in worldwide.

The Artificial Intelligence Alpha Group (AAG) is a newly formed, AI-native investment team dedicated to using artificial intelligence to drive superior investment performance. We are pioneering a new model of active investing that fuses domain expertise, proprietary data, and cutting-edge generative AI. AAG is a cross-functional team comprising experienced investors and expert technologists, working together to generate differentiated insights and deliver investment outperformance.

What impact can you make in the role?

We are seeking a Data Platform Engineer to design, implement, and manage the data foundation powering next-generation AI-driven research and investing systems. You will work closely with the ML Architect and Full-Stack Developer to ensure data pipelines, transformations, and databases are optimized for AI and analytical workflows.

This role combines hands-on data engineering with coordination across dedicated data resources to deliver high-quality, well-governed, and AI-ready datasets. The ideal candidate has strong technical expertise in data architecture and transformation, a practical understanding of AI-driven feature engineering, and experience operationalizing data pipelines for intelligent systems.

What will you do in this role?

• Collaborate with the ML Architect and Full-Stack Developer to design and maintain scalable data pipelines supporting AI model training, inference, and retrieval.
• Coordinate and oversee the work of dedicated data engineering resources (internal and external), ensuring quality, consistency, and timely delivery.
• Build and optimize data ingestion, cleaning, transformation, and enrichment workflows for both structured and unstructured datasets.
• Implement and manage data storage systems, including relational, vector, and graph databases, ensuring scalability, reliability, and integration with downstream applications.
• Support the development of feature transformation pipelines using both traditional and AI-assisted approaches.
• Implement data quality checks, lineage tracking, and governance practices to ensure reliable, compliant, and auditable use of data across systems.
• Collaborate with the Full-Stack AI Application Developer to integrate data services into production applications and APIs.
• Develop documentation, data dictionaries, and automated monitoring for data pipeline health and performance.
• Continuously explore modern data engineering frameworks and AI-enabled techniques and tools to improve productivity, scalability, and data workflow quality.

What makes you a successful candidate?

• Bachelor’s degree or higher in Computer Science, Data Engineering, or a related field.
• 8+ years of experience in data engineering, platform engineering, or data architecture, ideally in AI or analytics-intensive environments.
• Proficiency in Python, SQL, and modern databases and frameworks (e.g., PostgreSQL, DuckDB, Spark, Airflow, ClickHouse, Kafka or equivalent).
• Proficiency in extracting data from various formats (PDF, DOC, DOCX), with specific expertise in pulling key information from within tables and images, and experience with web scraping.
• Strong understanding of data modeling, feature engineering, and ELT pipeline design principles.
• Experience designing or working with vector databases or graph databases is preferred.
• Familiarity with data quality, metadata management, and governance frameworks.
• Working knowledge of cloud data environments (AWS/GCP/Azure) and containerized workflows (Docker, Kubernetes).
• Experience collaborating with AI/ML teams on data preparation and model-serving workflows.
• Strong coordination and communication skills to manage internal and external engineering resources.

Work at the Point of Impact

We need to be forward-looking to attract the right people to help us become the Leading Global Long-term Investor. Join our ambitious, agile, and diverse teams - be empowered to push boundaries and pursue innovative ideas, share your views, and be heard. Be anchored on our PRIME Values: Prudence, Respect, Integrity, Merit and Excellence, which guides us in how we make our day-to-day decisions. We strive to inspire. To make an impact.

Flexibility at GIC

At GIC, our offices are vibrant hubs for ideation, professional growth, and interpersonal connection. At the same time, we believe that flexibility allows us to do our best work and be our best selves. Thus, our teams come into the office four days per week to harness the benefits of in-person collaboration but have the flexibility to choose which days they work from home and adjust this arrangement as situational needs arise.

GIC is an equal opportunity employer

GIC is an equal opportunity employer, and we value diversity. We do not discriminate based on race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

Please email [e-mail] at any point of the application or interview process if adjustments need to be made due to a disability.