Trading Analytics & AI Platform Engineer

Crypto.com; Chicago (IL); Hybrid; USD 120,000 - 190,000; Full time

Benefits offered by this job

Competitive salary

Annual leave entitlement

401(k) plan with employer match

Health, dental, vision, and life/disab

Hybrid work setup

Internal mobility program

Job summary

Crypto.com is seeking an experienced Trading Analytics Developer to join our Quant Trading team. You will bridge traditional quantitative development with AI platform engineering, building scalable systems for data analytics and AI workloads.

You will design data pipelines, analytics engines, and AI tooling, while ensuring reliability, performance, and actionable insights across trading domains. Hybrid setup with strong collaboration across teams.

Qualifications

• 5+ years production experience with Python and Java in high-performance environments.
• Strong fundamentals: design, data structures, algorithms, data integrity, performance.
• Expertise with Linux, Github, and CI/CD practices.
• Proven experience with AWS cloud services and Kubernetes orchestration.
• Comfort with large-scale financial/trading datasets.

Responsibilities

• Design, build, and operate high-throughput data pipelines using Kafka, Flink, and ETL technologies.
• Develop analytics models for time-series and trading activity.
• Manage analytical databases (ClickHouse, MongoDB, BigQuery, Snowflake) with cost-aware architecture.
• Build and maintain AI platforms serving multiple trading teams.
• Create monitoring for data quality, freshness, and pipeline reliability.

Skills

Python

Java

Linux

GitHub

CI/CD

AWS

Kubernetes

SQL

Airflow

Kafka

Flink

Tools

Spark

ClickHouse

MongoDB

BigQuery

Snowflake

Grafana

TradingView

Jenkins

AMPS

LangGraph/A2A/MCP

Job description

Crypto.com is seeking an experienced Trading Analytics Developer to join our Quant Trading team. You will bridge traditional quantitative development with AI platform engineering, building scalable systems for data analytics and AI workloads.

You will design data pipelines, analytics engines, and AI tooling, while ensuring reliability, performance, and actionable insights across trading domains. Hybrid setup with strong collaboration across teams.