Data Engineer

1 week ago

Singapore Evolution Singapore Full time

Overview

Our client is a leading global trading company at the forefront of innovation in financial markets. They operate across multiple asset classes and thrive on data-driven decision-making. To strengthen their front office technology team, they are seeking a talented Data Engineer with strong expertise in front office or quantitative data .

The Role

As a Data Engineer, you will be responsible for designing, building, and optimizing data pipelines that power mission-critical trading and risk systems. You will work closely with quantitative analysts, traders, and technology teams to ensure data is clean, reliable, and scalable across the business.

This is an excellent opportunity for someone who thrives in a fast-paced, intellectually stimulating environment and wants to make a tangible impact in global markets.

Responsibilities

  • Design, develop, and maintain robust data pipelines to support trading, risk, and analytics platforms.
  • Collaborate with quants and front office teams to deliver high-quality data solutions .
  • Build and optimize scalable ETL/ELT processes for structured and unstructured datasets.
  • Implement best practices for data governance, quality, and automation.
  • Work with cloud-based platforms (ideally Azure) to modernize and scale infrastructure.
  • Partner with stakeholders across technology and the front office to deliver innovative solutions.

Requirements

  • Proven experience as a Data Engineer within a trading, financial services, or front office environment .
  • Strong knowledge of front office / quantitative data and its use in trading or risk functions.
  • Advanced skills in building data pipelines using modern frameworks (e.g., Spark, Kafka, Databricks, SQL, Python).
  • Solid understanding of database technologies (SQL and NoSQL).
  • Exposure to cloud platforms , ideally Azure (AWS or GCP also considered).
  • Excellent problem-solving skills and ability to work in fast-paced, high-pressure environments .

Seniority level

  • Mid-Senior level

Employment type

  • Full-time

Job function

  • Information Technology

Industries

  • Financial Services, Data Infrastructure and Analytics, and Technology, Information and Media

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