Fixed Income Data Specialist

S&P Global, Inc.; New York (NY); On-site; USD 54,000 - 77,000; Full time

Job summary

S&P Dow Jones Indices is seeking a data-focused professional to manage fixed income datasets, including bond terms, corporate actions, and reference data. You will collaborate with index managers to ensure timely updates and high data quality for index maintenance and production.

The role requires 1–3 years in financial data management, strong Python/SQL skills, and the ability to work with large datasets in a fast-paced, global environment.

Qualifications

• 1–3 years of experience in financial data management, data operations, index management, reference data, or a related function.
• Foundational understanding of fixed-income instruments and datasets.
• Strong analytical and quantitative skills with ability to work with large datasets.
• Proficiency in Python and SQL for data analysis, manipulation, and visualization.

Responsibilities

• Manage bond data products within the Fixed Income Data Group, including bond terms and conditions and corporate actions data, ensuring data quality and timely delivery for index production.
• Work with Fixed Income Index managers to deliver updates to securities within the relevant index universes.
• Onboard new data feeds and datasets, ensuring seamless integration into existing systems and adherence to quality metrics.
• Provide timely responses to client enquiries and assist in preparing reports related to fixed income data analysis.

Skills

Financial data management

Data operations

Index management

Python

SQL

Analytical skills

Communication

Education

Bachelor’s degree in finance, economics, mathematics, data science, or business

Tools

Python

SQL

Databricks

Power Automate

Job description

S&P Dow Jones Indices is seeking a data-focused professional to manage fixed income datasets, including bond terms, corporate actions, and reference data. You will collaborate with index managers to ensure timely updates and high data quality for index maintenance and production.

The role requires 1–3 years in financial data management, strong Python/SQL skills, and the ability to work with large datasets in a fast-paced, global environment.