Owns fraud and market-abuse detection models, rules, and partner-facing surveillance reporting across trading data. Investigates wash trading, collusion, hedging, reverse trading, and other suspicious activity; calibrates thresholds, validates false positives, maintains data quality, and produces evidence-based findings. Requires strong SQL, cloud data warehouse experience, futures and derivatives knowledge, anomaly detection expertise, and the ability to communicate findings to partners and executives.

Architect and own NinjaTrader’s foundational dbt data-model layer, establish modeling standards, and manage paid-media attribution. Develop AI-driven reporting, data-quality automation, agentic workflows, and self-service knowledge tools. Partner with Data and MarTech teams, prevent pipeline issues, scale models across business units and geographies, and mentor teammates while applying marketing measurement concepts such as CAC, LTV, and ROAS.

Design, build, and maintain scalable batch and real-time data pipelines and data lake architecture. Improve observability and SLOs, optimize ETL/ELT, develop dbt workflows, support event-driven architectures, integrate financial APIs, and collaborate with analytics and ML teams to deliver reliable, model-ready data products.