Trading Analytics Developer, Quantitative Trading

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

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

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.)