Data Engineer - Analyst, Risk & Quant Analytics

Company Introduction

Polymer Capital Management is a market-neutral, multi-manager investment platform based in and focused on Asia. Polymer combines established institutional support and deep knowledge of local financial markets with a dedication to discovering and developing the region's best investment talent. Polymer was established in conjunction with PAG, one of the world's largest Asia-focused alternative asset managers, in 2019.

Job Responsibilities / Job Brief

• We are looking for a Data Engineer to join our hedge fund and manage our data operations. You will be responsible for engaging with various data vendors, designing and implementing data pipelines, and ensuring data quality and security. You will also support the data infrastructure and pipelines of the fund.
• Design data pipelines to process various internal and external data according to the nature of the data and the needs of internal users.
• Make sure the data pipeline and storage solutions are performant and scalable.
• Implement automated data quality checks and an alert system to monitor and troubleshoot data issues.
• Provide adequate access control and usage audit solutions to ensure data security and compliance.
• Research and evaluate the latest data-related technologies and tools to keep our data platform updated and competitive.
• Collaborate with the investment and trading teams to understand their data needs and provide them with relevant and timely data access and delivery.

Requirements

• Bachelor's degree in Computer Science, Electronic Engineering, Data Engineering, or a related technical discipline.
• At least 3 years of experience in data engineering, preferably within the hedge fund, asset management, or financial services industry.
• Strong Python programming skills and proficiency in at least one statically typed programming language such as Java or C#.
• Hands-on experience with AWS-based data platforms and services, particularly S3.
• Strong experience with Apache Airflow for workflow orchestration and scheduling.
• Experience working with modern data storage formats and table formats, including Parquet and Apache Iceberg.
• Solid understanding of OLTP and OLAP database architectures and data modeling principles.
• Experience designing, building, and maintaining scalable data processing pipelines, including monitoring, alerting, troubleshooting, and recovery processes.
• Experience optimizing system performance, reliability, and operational stability in production environments.
• Strong knowledge of PostgreSQL, including database design, performance tuning, and operational best practices.
• Familiarity with distributed and parallel computing concepts and frameworks.
• Familiarity with Apache data technologies such as Spark and Kafka.
• Curiosity about financial markets and the ability to apply business context when designing and managing data solutions.
• Excellent communication, presentation, and interpersonal skills.
• A keen interest in and understanding of financial markets and hedge fund strategies.

Preferred Qualifications

• Experience with KDB+, StarRocks, or other specialized analytical databases.
• Experience working with real-time or streaming data processing systems.
• Experience conducting or supporting market microstructure and Level 2 (order book) data research.
• Experience building or maintaining alpha feature libraries, quantitative research datasets, or backtesting platforms.
• Experience developing internal web consoles, operational dashboards, or self-service data platforms.
• Experience working closely with quantitative researchers, portfolio managers, or trading teams.
• Experience with storage cost optimization and high-availability data infrastructure.