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