Quantitative Developer

Quantitative Developer at Fintonia Group

Fintonia Group is a Singapore a licensed asset manager, with a growing presence in Kuala Lumpur, combining a strong background in traditional finance with disruptive technology.

You will be joining a fun and fast-paced environment and will be working with a small team of seasoned industry professionals with experience working at top tier global investment banks and industry leaders.

Fintonia Group has launched the first Bitcoin tracker fund managed by a Monetary Authority of Singapore licensed fund manager.

We are seeking a Quantitative Developer to join our team in Kuala Lumpur. This hands-on role will contribute directly to the design and implementation of cloud-based trading infrastructure and data pipelines that support a diverse set of digital asset strategies. Yo will be working with a small, experienced team with backgrounds in global investment banks and hedge funds.

The ideal candidate is highly technical, fluent in Python, experienced with cloud systems and databases, and motivated to build scalable, reliable tools for real-time trading and analytics. This is a high-impact role that supports the organization's continued innovation in the digital asset space, offering strong career development in a dynamic and fast-paced environment.

The Role:

As a Quantitative Developer at Fintonia Group, you will build and maintain the infrastructure that powers the organization's systematic and discretionary trading strategies. This includes integrating with exchanges, managing real-time data pipelines, developing execution logic, and enabling effective risk monitoring and collateral management.

Your primary responsibilities will include:

Real-Time Trading Infrastructure

• Build and maintain Python-based execution systems for delta-neutral and options-based strategies
• Integrate with exchange APIs (REST, WebSocket) across spot, futures, perpetuals, and options markets
• Leverage cloud infrastructure (AWS, GCP, Azure) to deploy scalable and resilient trading systems
• Implement low-latency components for market data ingestion and order tracking

Cloud Data Engineering & Database Management

• Design and maintain cloud-native databases (e.g., PostgreSQL on RDS, BigQuery, Snowflake, TimescaleDB) for market, trade, and strategy data
• Develop efficient schemas for high-frequency data (order books, trades, funding rates, volatility metrics)
• Build automated data pipelines using tools like Airflow, Prefect, or AWS Step Functions
• Manage historical and real-time datasets for backtesting, signal generation, and performance reporting
• Ensure data quality, consistency, retention policies, and access controls across the platform
• Implement data versioning and metadata tracking to support research reproducibility

Monitoring, Risk Management & Dashboards

• Create dashboards using Streamlit, Dash, or Grafana to monitor strategies, markets, and system health
• Set up alerting systems for key risk indicators such as margin levels, volatility spikes, and basis dislocations
• Monitor database performance and query costs (especially in BigQuery/Snowflake), and optimize data usage

Qualifications and Experience

To be a successful applicant, you are likely to meet the following criteria:

• At least 3-5 years of experience in Python development, ideally in a trading or financial environment
• Strong experience with exchange APIs and real-time market data ingestion
• Practical experience with cloud-based databases (e.g., AWS RDS, Redshift, BigQuery, Snowflake)
• Proficient in SQL, schema design, and data modeling for high-frequency or time-series data
• Familiar with data lake and data warehouse concepts, partitioning strategies, and performance tuning
• Experience deploying to cloud environments (AWS/GCP/Azure), including Docker/Kubernetes and CI/CD pipelines
• Familiarity with infrastructure-as-code tools (e.g., Terraform, CloudFormation) is a plus
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field