Trading Analytics Developer, Quantitative Trading

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.

Job Responsibilities

Data Platform & Analytics

• Design, build, and operate high throughput batch and streaming data pipelines using Kafka, Flink, and ETL technologies
• Design and build unified analytics engine designed for processing large-scale data using Apache Spark and related tools
• Develop and optimize analytical data models for time-series, financial metrics, and trading activity
• Implement and manage analytical databases (ClickHouse, MongoDB, BigQuery, Snowflake, or similar) with cost-aware architecture
• Build idempotent data pipelines with robust backfill and reconciliation capabilities
• Create comprehensive monitoring for data quality, freshness, and pipeline reliability

AI Platform Development

• Design, build, and operate internal AI platforms serving multiple trading teams
• Build reusable AI tooling including standardized RAG pipelines, prompt management, and self-service workflows
• Create and maintain agent systems using modern frameworks (LangGraph, A2A, MCP) with focus on controllability and auditability

Job Requirements

Mandatory Foundations

• 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

Data Platform Expertise

• 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, web-based interactive dashboards and BI tools etc.
• Kafka, Flink, and event processing in production environments

AI Platform Capabilities

• 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

Preferred Qualifications

Financial/Trading Domain

• 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

Professional Attributes

• Excellent problem-solving skills with ability to perform under pressure
• Strong communication skills for cross-team collaboration
• Proactive approach to system reliability and performance optimization
• Continuous learning mindset in rapidly evolving AI/ML landscape
• Balance of practical engineering rigor with innovative solution development