Trading Analytics Developer, Quantitative Trading

Job description

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