Jobs at Edelweiss Global Markets

Build and maintain Power BI dashboards, reports, data models, and DAX measures for trading and business insights. Extract, transform, validate, cleanse, and analyze data using SQL while supporting the organization’s data platform. Collaborate with stakeholders to translate business requirements into reporting solutions and progressively contribute to AWS-based data workflows, cloud storage, and data pipelines.

Designs, builds, and optimizes scalable data platforms, distributed systems, and high-volume ETL pipelines supporting trading and business operations. Develops solutions using Java, Python, Kafka, microservices, and modern databases while ensuring reliability, governance, data quality, and performance. Automates operational processes, improves application scalability, collaborates with trading and technology teams, and mentors junior engineers.

Develop and deploy systematic trading strategies across asset classes, including alpha generation, market microstructure analysis, backtesting, validation, risk management, and live performance monitoring. Collaborate with Portfolio Managers on strategy improvements and capital allocation. The role requires strong quantitative and statistical expertise, programming in Python or C++, and a deep understanding of market regimes and systematic research.

Own and scale a systematic multi-asset trading portfolio valued at more than $10 million. Responsibilities include alpha research, strategy engineering, portfolio construction, execution oversight, risk management, and leading researchers and analysts. The role requires adapting exposures to changing market regimes, improving models, developing new strategies, and delivering strong risk-adjusted returns while maintaining disciplined capital allocation.

Develop backtesting, simulation, and live trading systems in partnership with quantitative researchers and traders. Build scalable, fault-tolerant infrastructure for multi-asset, multi-geography strategy deployment, maintain data validation and hygiene pipelines, optimize performance, and manage cloud-based research infrastructure. The role requires production-quality C++ and Python development, numerical computing, large-scale simulations, tick-level market data processing, and fast I/O pipelines.