Senior Data Engineer

mirae asset securities (singapore) pte. ltd.; Singapore; On-site; SGD 140,000 - 200,000; Full time

Job summary

Mirae Asset Securities (Singapore) Pte. Ltd. is seeking a Senior Data Engineer to design and operate the data backbone for its global investment platform. You will handle market data from multiple vendors and ensure data correctness, completeness, and cross-time-zones consistency.

Based in Singapore, you will collaborate with platform engineering and investment teams across global offices to deliver reliable data products that inform trading decisions and risk management.

Qualifications

• 7+ years of experience designing and operating production data pipelines at scale.
• Hands-on experience with financial market data and cross-asset coverage.
• Strong cloud data platform experience (AWS, GCP, Azure, or Snowflake) and SQL proficiency.

Responsibilities

• Design and build data pipelines on Snowflake and Airflow that ingest, normalize, and serve global market data from multiple vendors.
• Own data infrastructure on cloud, including reliability, cost, and performance.
• Build automated data quality and validation systems for financial data.
• Partner with quantitative researchers and investment professionals to deliver data products they can trust.
• Contribute to platform-level decisions on architecture, tooling, and engineering standards.

Skills

SQL

Relational data modeling

Data pipeline design

Leadership

Communication

Tools

Snowflake

Airflow

AWS

GCP

Azure

Job description

About the Team

Mirae Asset Securities (Singapore) Pte. Ltd. is hiring a Senior Data Engineer to support Mirae Asset group’s AI-driven global investment platform. The goal is to provide a stable platform covering a broad range of areas, from data to serving, built on a global infrastructure.

About the Role

We are looking for a Senior Data Engineer to design and operate the data backbone supporting the group’s global investment and trading activities. You will work with market data from a wide range of global vendors, covering markets across regions and asset classes. The challenge here is not latency. Itis correctness, completeness, and consistency across markets, time zones, and corporate actions, where the data you build flows into real investment decisions.

This role is based in Singapore and works closely with the group’s platform engineering and investment teams across global offices.

What You Will Do

• Design and build data pipelines on Snowflake and Airflow that ingest, normalize, and serve global market data from multiple vendors.
• Own data infrastructure on cloud, including reliability, cost, and performance.
• Build automated data quality and validation systems for financial data.
• Partner with quantitative researchers and investment professionals to deliver data products they can trust.
• Contribute to platform-level decisions on architecture, tooling, and engineering standards.

Required

• 7+ years of experience designing and operating production data pipelines at scale.
• Hands‑on experience working with financial market data in an investment management, securities, hedge fund, or capital markets environment, covering asset classes such as equities, fixed income, derivatives, or alternatives.
• Deep hands‑on experience with cloud data platforms (AWS, GCP, Azure, or Snowflake).
• Strong SQL and relational data modeling fundamentals.
• Track record of leading the design of data systems that other engineers, analysts, or researchers depend on.
• Clear written and verbal communication, including the ability to explain technical trade-offs.

Strongly Preferred

• Experience integrating data from global market data vendors (Bloomberg, LSEG, FactSet, MSCI, S&P, or similar).
• Experience handling cross‑vendor data reconciliation, corporate actions, and point‑in‑time correctness across global markets.
• Working proficiency in English (our team collaborates with global offices).

Why This Role

• Global scope, one platform: You will work on data infrastructure that spans global markets rather than a single region.
• Real investment impact: The data you build flows into actual investment and risk decisions.
• Greenfield where it matters: The platform is still being built, with room to shape how it is designed.