Trading Analytics Developer, Quantitative Trading

Crypto; Hong Kong; On-site; HKD 900,000 - 1,800,000; Full time

Benefits offered by this job

Competitive salary

Medical insurance package with depend.

Annual leave entitlement

Flexi-work hours; hybrid or remote set

Internal mobility program

Crypto.com Visa card

Region-based benefits

Job summary

Crypto.com is seeking an experienced Trading Analytics Developer to join the Quant Trading team in Hong Kong. You will design and operate high-throughput data pipelines, analytical models, and AI-enabled platforms supporting multiple trading teams.

The role blends Python/Java development with modern AI infrastructure, emphasizing reliability, performance, and actionable insights in a fast-paced crypto environment.

Qualifications

• 5+ years production experience with both Python and Java in high-performance environments
• Strong software engineering fundamentals: system design, data structures, algorithms, data integrity, accuracy and performance optimization
• Expertise in Linux, Github, and modern CI/CD practices
• Proven experience with AWS cloud services and Kubernetes orchestration
• Comfort working with large-scale, complex datasets in financial/trading contexts
• Advanced SQL with window functions and query optimization, realtime data synchronization together with database design and infrastructure support
• Experience with data workflow and messaging orchestration (Airflow, Jenkins, AMPS etc.)
• Metric design and implementation for trading analytics (PnL, risk, balance and trade reconciliation, backfill and performance tuning)
• Time-series data visualization with Grafana, TradingView and BI tools
• Kafka, Flink, and event processing in production environments
• Vector search system design and optimization (recall/latency/memory trade-offs)
• Retrieval system evaluation methodologies and quality frameworks
• RAG pipeline architecture and optimization techniques
• LLMOps practices including model lifecycle and prompt management
• Experience with AI agent frameworks in production settings like A2A and MCP
• LangGraph / LangChain to build AI workflow and to connect AI models with data and tools to create smarter applications
• Experience in trading systems, quantitative finance, or financial technology
• Understanding of market data, data subscription using Rest API / Web Socket
• Knowledge of cryptocurrency markets, defi, and related technologies

Responsibilities

• Data Platform & Analytics: Design, build, and operate high throughput batch and streaming data pipelines using Kafka, Flink, and ETL technologies
• Data Platform & Analytics: Develop and optimize analytical data models for time-series, financial metrics, and trading activity
• Data Platform & Analytics: Implement and manage analytical databases (ClickHouse, MongoDB, BigQuery, Snowflake, or similar) with cost-aware architecture
• Data Platform & Analytics: Build idempotent data pipelines with robust backfill and reconciliation capabilities
• Data Platform & Analytics: Create comprehensive monitoring for data quality, freshness, and pipeline reliability
• AI Platform Development: Design, build, and operate internal AI platforms serving multiple trading teams
• AI Platform Development: Develop vector search systems with optimized HNSW indexing and hybrid retrieval capabilities
• AI Platform Development: Implement evaluation frameworks for retrieval quality (Recall@K, MRR, nDCG) and RAG systems
• AI Platform Development: Build reusable AI tooling including standardized RAG pipelines, prompt management, and self-service workflows
• AI Platform Development: Create and maintain agent systems using modern frameworks (LangGraph, A2A, MCP) with focus on controllability and auditability
• Mandatory Foundations: 5+ years production experience with both Python and Java in high-performance environments
• Mandatory Foundations: Strong software engineering fundamentals: system design, data structures, algorithms, data integrity, accuracy and performance optimization
• Mandatory Foundations: Expertise in Linux, Github, and modern CI/CD practices
• Mandatory Foundations: Proven experience with AWS cloud services and Kubernetes orchestration
• Mandatory Foundations: Comfort working with large-scale, complex datasets in financial/trading contexts
• Data Platform Expertise: Advanced SQL with window functions and query optimization, realtime data synchronization together with database design and infrastructure support
• Data Platform Expertise: Experience with data workflow and messaging orchestration (Airflow, Jenkins, AMPS etc.)
• Data Platform Expertise: Metric design and implementation for trading analytics (PnL, risk, balance and trade reconciliation, backfill and performance tuning)
• Data Platform Expertise: Time-series data visualization with Grafana, TradingView and BI tools
• Data Platform Expertise: Kafka, Flink, and event processing in production environments
• AI Platform Capabilities: Vector search system design and optimization (recall/latency/memory trade-offs)
• AI Platform Capabilities: Retrieval system evaluation methodologies and quality frameworks
• AI Platform Capabilities: RAG pipeline architecture and optimization techniques
• AI Platform Capabilities: LLMOps practices including model lifecycle and prompt management
• AI Platform Capabilities: Experience with AI agent frameworks in production settings like A2A and MCP
• AI Platform Capabilities: LangGraph / LangChain to build AI workflow and to connect AI models with data and tools to create smarter applications
• AI Platform Capabilities: Experience in trading systems, quantitative finance, or financial technology
• AI Platform Capabilities: Understanding of market data, data subscription using Rest API / Web Socket
• AI Platform Capabilities: Knowledge of cryptocurrency markets, defi, and related technologies

Skills

Python

Java

Linux

GitHub

CI/CD

AWS

Kubernetes

SQL

Kafka

Flink

Tools

ClickHouse

MongoDB

BigQuery

Snowflake

Kafka

Flink

Airflow

Jenkins

AMPS

Grafana

Job description

Overview

The Quant Trading team is responsible for trading and managing risks associated with different crypto products, including spots and derivatives. The team develops and implements trading strategies in fast-paced and complex trading environments. We are seeking an experienced Trading Analytics Developer to join our Quant Trading team and play a pivotal role in advancing our data and AI infrastructure. This role combines traditional quantitative development with cutting-edge AI platform engineering, focusing on building robust, scalable systems that serve both data analytics and artificial intelligence workloads. The ideal candidate will bridge the gap between high-performance trading systems and modern AI capabilities, ensuring reliability, performance, and actionable insights across both domains.

Responsibilities

• Data Platform & Analytics: Design, build, and operate high throughput batch and streaming data pipelines using Kafka, Flink, and ETL technologies
• Data Platform & Analytics: Develop and optimize analytical data models for time-series, financial metrics, and trading activity
• Data Platform & Analytics: Implement and manage analytical databases (ClickHouse, MongoDB, BigQuery, Snowflake, or similar) with cost-aware architecture
• Data Platform & Analytics: Build idempotent data pipelines with robust backfill and reconciliation capabilities
• Data Platform & Analytics: Create comprehensive monitoring for data quality, freshness, and pipeline reliability
• AI Platform Development: Design, build, and operate internal AI platforms serving multiple trading teams
• AI Platform Development: Develop vector search systems with optimized HNSW indexing and hybrid retrieval capabilities
• AI Platform Development: Implement evaluation frameworks for retrieval quality (Recall@K, MRR, nDCG) and RAG systems
• AI Platform Development: Build reusable AI tooling including standardized RAG pipelines, prompt management, and self-service workflows
• AI Platform Development: Create and maintain agent systems using modern frameworks (LangGraph, A2A, MCP) with focus on controllability and auditability
• Mandatory Foundations: 5+ years production experience with both Python and Java in high-performance environments
• Mandatory Foundations: Strong software engineering fundamentals: system design, data structures, algorithms, data integrity, accuracy and performance optimization
• Mandatory Foundations: Expertise in Linux, Github, and modern CI/CD practices
• Mandatory Foundations: Proven experience with AWS cloud services and Kubernetes orchestration
• Mandatory Foundations: Comfort working with large-scale, complex datasets in financial/trading contexts
• Data Platform Expertise: Advanced SQL with window functions and query optimization, realtime data synchronization together with database design and infrastructure support
• Data Platform Expertise: Experience with data workflow and messaging orchestration (Airflow, Jenkins, AMPS etc.)
• Data Platform Expertise: Metric design and implementation for trading analytics (PnL, risk, balance and trade reconciliation, backfill and performance tuning)
• Data Platform Expertise: Time-series data visualization with Grafana, TradingView and BI tools
• Data Platform Expertise: Kafka, Flink, and event processing in production environments
• AI Platform Capabilities: Vector search system design and optimization (recall/latency/memory trade-offs)
• AI Platform Capabilities: Retrieval system evaluation methodologies and quality frameworks
• AI Platform Capabilities: RAG pipeline architecture and optimization techniques
• AI Platform Capabilities: LLMOps practices including model lifecycle and prompt management
• AI Platform Capabilities: Experience with AI agent frameworks in production settings like A2A and MCP
• AI Platform Capabilities: LangGraph / LangChain to build AI workflow and to connect AI models with data and tools to create smarter applications
• Financial/Trading Domain: Experience in trading systems, quantitative finance, or financial technology
• Financial/Trading Domain: Understanding of market data, data subscription using Rest API / Web Socket
• Financial/Trading Domain: Knowledge of cryptocurrency markets, defi, and related technologies
• Professional Attributes: Excellent problem-solving skills with ability to perform under pressure
• Professional Attributes: Strong communication skills for cross-team collaboration
• Professional Attributes: Proactive approach to system reliability and performance optimization
• Professional Attributes: Continuous learning mindset in rapidly evolving AI/ML landscape
• Professional Attributes: Balance of practical engineering rigor with innovative solution development

Qualifications

• 5+ years production experience with both Python and Java in high-performance environments
• Strong software engineering fundamentals: system design, data structures, algorithms, data integrity, accuracy and performance optimization
• Expertise in Linux, Github, and modern CI/CD practices
• Proven experience with AWS cloud services and Kubernetes orchestration
• Comfort working with large-scale, complex datasets in financial/trading contexts
• Advanced SQL with window functions and query optimization, realtime data synchronization together with database design and infrastructure support
• Experience with data workflow and messaging orchestration (Airflow, Jenkins, AMPS etc.)
• Metric design and implementation for trading analytics (PnL, risk, balance and trade reconciliation, backfill and performance tuning)
• Time-series data visualization with Grafana, TradingView and BI tools
• Kafka, Flink, and event processing in production environments
• Vector search system design and optimization (recall/latency/memory trade-offs)
• Retrieval system evaluation methodologies and quality frameworks
• RAG pipeline architecture and optimization techniques
• LLMOps practices including model lifecycle and prompt management
• Experience with AI agent frameworks in production settings like A2A and MCP
• LangGraph / LangChain to build AI workflow and to connect AI models with data and tools to create smarter applications
• Experience in trading systems, quantitative finance, or financial technology
• Understanding of market data, data subscription using Rest API / Web Socket
• Knowledge of cryptocurrency markets, defi, and related technologies

Benefits

• Competitive salary
• Medical insurance package with extended coverage to dependents
• Attractive annual leave entitlement including: birthday, work anniversary
• Work Flexibility: Flexi-work hour and hybrid or remote set-up
• Aspire career alternatives through us. Our internal mobility program can offer employees a diverse scope.
• Work Perks: crypto.com visa card provided upon joining
• Crypto.com benefits packages vary depending on region requirements; learn more from our talent acquisition team.

About Crypto.com

Crypto.com is an equal opportunities employer and we are committed to creating an environment where opportunities are presented to everyone in a fair and transparent way. Crypto.com values diversity and inclusion, seeking candidates with a variety of backgrounds, perspectives, and skills that complement and strengthen our team. Personal data provided by applicants will be used for recruitment purposes only.