FINANCIAL DATA INSTRUMENT SPECIALIST

Position description

Financial Data Instrument Specialist in Lisbon, Operations Department (Full-time).

About the role

We are looking for a detail-oriented and proactive Financial Instrument Data Specialist to join our Operational Services Middle Office team. In this role, you will be responsible for ensuring the integrity, accuracy, and completeness of financial instrument reference data used throughout the organization. You will work closely with IT and other internal stakeholders to improve data quality and identify opportunities for process improvement and automation.

Tasks

• Monitoring and validation of incoming data feeds from financial instrument data providers such as Bloomberg, Refinitiv, etc.
• Identifying opportunities for automating and managing instrument data processes to achieve a very high degree of automation.
• Defining, tracking, and reporting on key performance indicators (KPIs) related to data completeness, accuracy, and timeliness.
• Collaborate with IT and other departments to ensure a smooth flow of data and the timely resolution of issues.
• Participation in projects related to reference data strategy, system integration, and process optimization.
• Ensuring a high standard of data quality to enable smooth transaction processing and risk management.

Requirements

• Experience with financial services statistical data, ideally in a data management or operations-oriented role.
• Familiarity with financial instruments across various asset classes (e.g., stocks, bonds, derivatives, etc.).
• A strong analytical mind with an eye for detail and a commitment to data quality.
• Experience with data systems or market data providers (e.g., Bloomberg, Refinitiv, etc.).
• Strong communication and collaboration skills, with the ability to work effectively within operations and IT teams.

Nice to Have

• Proficiency in Python or similar languages and data analysis tools; knowledge of SQL or scripting languages is a plus.
• An understanding of regulatory requirements that affect reference data is advantageous.
• Previous experience in defining and monitoring data quality KPIs.