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Data Engineer ($40-55k + bonus) - investment bank

Job description

It is a leading financial institution with solid business across APAC.

Responsibilities

  • Design, build, and maintain scalable data pipelines and ETL/ELT processes to support trading, risk, operations, and market data analytics.
  • Develop high‑quality, production‑grade Python code for data ingestion, cleansing, transformation, and automation.
  • Integrate data from trading systems, market data vendors, internal platforms, and external APIs; ensure data reliability, accuracy, and timeliness.
  • Optimize data workflows, improve performance, and enhance data quality through monitoring, validation, and automation.
  • Collaborate with business analysts, data teams, and technology partners to understand requirements and deliver robust data solutions.
  • Build and maintain data models, schemas, and documentation to support analytics, dashboards, regulatory reporting, and downstream applications.
  • Support cloud or on‑premise data platforms, including scheduling, orchestration, version control, and CI/CD practices.
  • Troubleshoot data issues, perform root‑cause analysis, and ensure high availability and integrity of critical data pipelines.

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Data Analytics, or a related discipline.
  • 4-8 years of hands‑on experience as a Data Engineer or similar role within financial institutions, Big 4 consulting, or large enterprises.
  • Strong programming proficiency in Python (data manipulation, automation, API integrations, ETL frameworks).
  • Good knowledge of SQL and experience working with relational databases and/or cloud data platforms.
  • Experience with ETL/ELT tools, workflow orchestration, and data pipeline design.
  • Familiarity with distributed systems, data warehousing concepts, and performance optimization.
  • Exposure to capital markets data (trading, market data, risk data, pricing) is preferred; strong interest in financial markets is required.
  • Experience with DevOps tools (Git, CI/CD pipelines, containers) is an advantage.
  • Strong analytical and problem‑solving skills with attention to detail.
  • Strong commands of Chinese and English will be desired.