Senior Staff - IT Data Engineering and Analytics

With more than 5,400 employees serving over 80,000 commercial, institutional, and payments clients, and more than 400,000 retail accounts, from more than 80 offices spread across six continents, we’re a Fortune-500, Nasdaq-listed provider, connecting clients to the global markets – focusing on innovation, human connection, and providing world-class products and services to all types of investors.

At StoneX, we offer you the opportunity to be part of an institutional-grade financial services network that connects companies, organizations, and investors to the global markets ecosystem. As a team member, you'll benefit from our unique blend of digital platforms, comprehensive clearing and execution services, personalized high-touch support, and deep industry expertise. Elevate your career with us and make a significant impact in the world of global finance.

• Expertise in Microsoft SQL Server
• Advanced SQL query optimization and performance tuning
• Experience with stored procedures, indexing, partitioning, and database design
• Knowledge of NoSQL databases (MongoDB, Cassandra, Redis) is preferred
• Experience handling large-scale market and risk datasets
• Hands-on experience with Databricks for large-scale data processing, including Spark-based ETL/ELT pipelines, Delta Lake, and Unity Catalog
• Modern data engineering skills, including workflow orchestration (Airflow), data pipeline design, data quality/observability, and building scalable batch and streaming data platforms

• Experience integrating AI/ML models into data platforms, automation workflows, and risk applications
• Exposure to Large Language Models (LLMs) and Generative AI frameworks (e.g., Azure OpenAI, LangChain, Copilot)
• Experience applying AI-driven observability, anomaly detection, and intelligent automation to platform reliability
• Familiarity with responsible AI principles and model governance in a regulated financial services environment

• Experience with cloud platforms such as Azure or AWS
• CI/CD implementation using Azure DevOps, GitHub Actions, or Jenkins
• Containerization using Docker and Kubernetes

• Python for analytics and risk calculations
• Databricks/Spark
• Quantitative finance exposure
• AI/ML applications in Risk Management
• Low-latency trading or risk systems
• Exposure to OpenTelemetry and modern observability platforms

Ideal Profile: Senior Technical Lead who combines deep C#/Python engineering expertise, financial risk domain knowledge, solution architecture capabilities, and people leadership experience to deliver mission-critical Risk Technology platforms in a regulated financial environment