Finance Data Engineer

FIRST PLUS ASSET MANAGEMENT PTE. LTD.; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A financial management firm based in Singapore is seeking a Finance Data Engineer to join their Data Intelligence Team. This role involves building and maintaining data pipelines, developing AI models, and supporting financial datasets to influence strategic investment decisions. Ideal candidates should possess a Bachelor's or Master's degree in Computer Science or a related field, with strong analytical skills and proficiency in Python. The position offers hands-on experience in financial data management and opportunities to impact automation and operational efficiency.

Benefits

Hands-on exposure to AI applications in finance

Opportunity to contribute to impactful projects

Direct impact on operational efficiency

Qualifications

• Bachelor's or Master's in Computer Science, Data Science, or related field.
• Relevant experience in financial data analytics.
• Strong foundation in Python for AI/ML model development.

Responsibilities

• Build and maintain core data pipelines for financial datasets.
• Integrate internal and external APIs for data access.
• Provide support for market data processing and ad-hoc queries.

Skills

Strong analytical skills

Python for data analysis

Understanding of financial instruments

Experience with APIs

Education

Bachelor’s or Master’s degree in Computer Science or related field

Tools

AWS databases

REST APIs

POSTMAN

Job description

About the Role

We are seeking a Finance Data Engineer with strong analytical and technical skills to join our team. This role offers the opportunity to work at the intersection of finance and technology by building AI-driven solutions and managing financial datasets to support strategic investment decisions.

As part of our Data Intelligence Team, you will play a key role in designing, implementing, and optimizing data pipelines, AI models, and analytical tools that drive business insights and improve investment performance.

Key Responsibilities

• Build & Maintain Core Data Pipelines: Work with AWS databases to manage, clean, and query large financial datasets; optimize database queries to ensure efficiency in extracting and processing data.
• REST API & System Integration: Maintain internal and external REST APIs used for market data, fund data, and operational systems via POSTMAN or EC2.
• Financial Data Processing & Ad-hoc Support: Handle market data extractions, transformations, fund performance requests, and reusable scripts for recurring queries.
• Collaboration: Act as a central point of accountability for data pipelines and data integrity; work closely with portfolio managers, analysts, and technology teams to translate business needs into data-driven solutions; contribute to ongoing projects and propose innovative ideas that leverage AI and automation in finance.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science and Business Analytics or a related field.
• Relevant experience in financial data analytics or technology roles.
• Strong foundation in Python for data analysis and AI/ML model development.
• Experienced with APIs: REST, JSON, authentication methods (OAuth, tokens).
• Experienced with VPN connectivity, cloud workflows, and secure data access.
• Completed Projects related to machine learning and deep learning concepts is a plus.
• Understanding of financial instruments and asset management concepts.

What You’ll Gain

• Hands-on exposure to AI applications in finance.
• Practical experience in financial data management and asset performance analysis.
• Opportunity to contribute to impactful projects that shape investment decisions.
• Direct impact on automation, operational efficiency, and data quality across the organization.

Interviewing Process

• Pre-Selection: Take-home technical assessment focused on Data Structures & Algorithms (DSA).
• Round 1 – Technical Interview: Discussion of the take-home assessment and evaluation of core technical knowledge (DSA, APIs, VPNs, Cloud Computing).
• Round 2 – Fit Interview: Assessment of role alignment, problem-solving approach, and cultural fit.
• Round 3 – Management Interview: Final discussion with leadership focusing on experience, expectations, and growth potential.