Reference Data Business Analyst

Key responsibilities include defining functional specifications, validating data, managing project lifecycles, liaising between business and technical teams, and ensuring compliance with regulatory standards. Strong analytical, communication, and problem-solving skills, along with technical skills like SQL, are essential for success in this role.

REFERENCE DATA EXP AT INVESTMENT BANKING IS MANDATORY

Key Responsibilities

Requirements Gathering :

Elicit and document business needs for reference data systems, translating them into detailed functional and technical specifications for developers.

Data Analysis & Quality :

Perform data analysis to ensure the accuracy, completeness, and consistency of reference data, identifying and resolving exceptions and inconsistencies.

System Design & Implementation :

Collaborate on the design, development, and implementation of reference data solutions and related processes.

Project Management :

Manage the project lifecycle for reference data initiatives, including planning, status reporting, and stakeholder communication.

Liaison & Communication :

Act as a key point of contact between business stakeholders (front and back office), technical teams, and developers.

Process Improvement :

Identify opportunities for process improvements and automation to enhance efficiency and data quality.

Regulatory Compliance :

Ensure reference data management practices comply with regulatory requirements and internal policies.

Documentation & Reporting :

Create and maintain project documentation, user guides, and status reports for various stakeholders.

Essential Skills

Data Analysis :

Proficient in analyzing data to identify trends, issues, and improvements, often using tools like SQL, Python, or Excel.

Business Acumen :

Strong understanding of financial products, trading activities, and the data lifecycle.

Communication :

Excellent written and verbal communication skills for effectively conveying requirements and collaborating with diverse teams.

Problem-Solving :

Ability to conduct root cause analysis and develop effective solutions for data-related issues.

Technical Proficiency :

Familiarity with data modeling, data governance, and data management principles.

Project Management :

Experience in managing projects, facilitating workshops, and overseeing UAT.