JOB DESCRIPTION

Corporate Treasury lies at the heart of Goldman Sachs, manages the firm’s liquidity, funding, balance sheet and capital to maximize net interest income and return on equity through liquidity portfolio management, liability planning & execution, resource allocation, and asset liability management.

Our Corporate Treasury Engineering team is a world leader in developing quantitative techniques and technological solutions that solve complex and commercial business problems. The team owns the analytics, methodologies, and infrastructure that facilitate the execution of Corporate Treasury mandate, creating and utilizing models and reporting to inform optimization and risk management decisions.

Data Office team within Corporate Treasury Engineering performs governance function on all aspects related to data – collection, persistence and distribution. Additionally, the team works on data uplift projects that span across multiple teams within as well as outside of Corporate Treasury division.

Responsibilities:

• Understand the data consumed within Corporate Treasury
• Identify data gaps, data uplift and data consolidation opportunities
• Work with multiple data consumers to understand the data requirements
• Work with multiple data providers to source the data for Corporate Treasury needs
• Create logical data models to represent financial assets
• Direct the control and governance requirements for data quality
• Implement data quality controls

Qualifications:

• Bachelors’ or Master’s degree in Computer Science, Mathematics, Electrical Engineering or related technical discipline
• Strong programming experience in Python and/or a compiled language (e.g. C, C++, Java)
• Strong proficiency with SQL
• 1-3 years of relevant, continuous experience
• Experience at optimizing large complicated SQL statements
• Comfortable multi-tasking, managing multiple stakeholders and working as part of a team
• Excellent communication skills including experience speaking to technical and business audiences and working globally
• Familiarity with financial markets and financial assets is a plus
• Familiarity with tools that can aid with troubleshooting and performance optimization of SQL queries is a plus