Senior Analytics Developer - Data Platform, Quant Analytics, Java, Python

Crypto.com; United States; Remote; USD 90,000 - 150,000; Full time

Job summary

An established industry player is seeking a seasoned Quantitative Developer to join their dynamic trading team. This role involves developing high-performance applications using Java and Python, while also managing cloud-based solutions on AWS. You will work in a fast-paced environment, leveraging your expertise in event processing and messaging technologies like Kafka and Flink. The ideal candidate will possess strong quantitative analysis skills, enabling them to provide actionable insights through advanced data visualization tools such as Prometheus and Grafana. If you're ready to make an impact in the exciting world of crypto trading, this opportunity is perfect for you.

Qualifications

• 5+ years experience in Java and Python development.
• Strong knowledge of AWS and Kubernetes management.
• Expertise in quantitative data analysis and event processing.

Responsibilities

• Develop applications in Java and Python focusing on performance.
• Design and manage cloud solutions on AWS for scalability.
• Conduct quantitative analysis to improve system performance.

Skills

Java

Python

Event Processing

Messaging Queues

AWS

Kubernetes

Quantitative Data Analysis

Problem-Solving

Communication Skills

Tools

Kafka

Flink

Complex Event Processing (CEP)

Prometheus

Grafana

Job description

The Quant Trading team is responsible for trading and managing risks associated with different crypto products, including spots and derivatives. The team develops and implements trading strategies in fast-paced and complex trading environments.

Responsibilities

• Develop and enhance applications utilizing Java and Python, with a focus on performance and scalability.
• Implement and maintain event processing and messaging queues, with expertise in Kafka, Flink, and Complex Event Processing (CEP) technologies.
• Design, deploy, and manage cloud-based solutions on AWS, ensuring high availability and scalability.
• Administer and optimize Kubernetes (k8s) clusters for container orchestration and management.
• Conduct quantitative data analysis, leveraging a robust quantitative analytic framework to inform decision-making and improve system performance.
• Develop, maintain, and utilize tools like Prometheus and Grafana for effective time-series data visualization and monitoring.
• Create and manage statistical reports and reporting systems, ensuring they provide actionable insights.
• Collaborate closely with various teams to automate and streamline trading, reconciliation, and analytics workflows.
• Provide advanced technical support and troubleshooting for developed systems and applications.

Requirements

• Minimum of 5 years of professional experience in both Java and Python development.
• Profound knowledge in event processing and messaging queues, including experience with Kafka, Flink, and CEP technologies.
• Strong experience with AWS cloud services and proficient in managing Kubernetes environments.
• Demonstrated ability in quantitative data analysis and familiarity with quantitative analytic frameworks.
• Skilled in the use of Prometheus and Grafana for time-series data visualization and monitoring.
• Experience in developing and maintaining reporting systems with a strong grasp of statistical report generation.
• Prior experience in a trading or financial environment is beneficial but not mandatory.
• Solid understanding of system design, data structures, and algorithms.
• Good problem-solving skills and the ability to work under pressure in a fast-paced environment.
• Excellent communication and teamwork skills.

Nice to Have:

• Familiarity with Aeron messaging and Simple Binary Encoding (SBE) protocol.
• Knowledge of C++ and experience with FPGA programming.
• Understanding of cryptocurrency markets and related technologies.
• Experience with network programming (TCP, WebSocket).
• Experience with Linux system administration and optimization.
• Previous experience with technologies such as Boost, ZeroMQ, MongoDB, Protobuffer.