Data Engineer with Capital Market/Derivatives

Job Title

Develop, build, and maintain scalable data pipelines using Python, PySpark, and Databricks to process large volumes of financial data.

Design and optimize data warehouses (DWH) to support analytics and reporting in capital markets.

Work closely with quantitative analysts and traders to transform raw data into insightful models and reports.

Handle derivatives data and ensure accurate, efficient data transformations and calculations.

Implement best practices for data quality, validation, and security across all data workflows.

Collaborate with cross-functional teams to integrate data sources and improve data governance.

Monitor, troubleshoot, and optimize data processes to ensure performance, reliability, and compliance with financial standards.

Proven experience in capital markets data management and derivatives.

Strong proficiency in Python, PySpark, and Databricks environment.

Hands-on experience with data warehousing solutions and architecture.

Familiarity with financial instruments, derivatives, and related data structures.

Experience working with large-scale distributed data processing systems.

Knowledge of data governance, security standards, and compliance in a financial environment.

Excellent problem-solving skills, attention to detail, and communication abilities.