Expert

The Expert is responsible for providing subject matter expertise across Reference Data processes, ensuring data quality, operational excellence, process standardization, and continuous improvement.

Reporting to the Operations Manager, the role supports business operations through effective governance, issue resolution, stakeholder engagement, and the adoption of AI and automation solutions to enhance efficiency and accuracy.

Key Responsibilities Act as the primary SME for Reference Data processes, policies, standards, and controls.

Provide expert guidance and support on complex Reference Data queries, exceptions, and issue resolution.

Monitor data quality, operational performance, and key metrics, identifying trends, risks, and improvement opportunities.

Drive First Time Right (FTR) performance through root cause analysis, corrective actions, and continuous improvement initiatives.

Leverage AI, automation, and analytics tools to improve productivity, data accuracy, and operational efficiency.

Develop, maintain, and enhance SOPs, process documentation, business rules, and knowledge repositories.

Collaborate with Operations, Quality, Technology, and Business stakeholders to ensure data integrity, compliance, and customer satisfaction.

Conduct training, coaching, and knowledge-sharing sessions to strengthen Reference Data domain expertise across teams.

Support process optimization, data governance, and transformation initiatives.

Ensure timely communication, risk management, and escalation of critical operational and data-quality issues.

Foster a culture of quality, accountability, innovation, and continuous improvement.

3–6 years of relevant experience in Reference Data Governance, or related operational domains.

Strong understanding of Reference Data lifecycle, data governance, data quality controls, and operational processes.

Demonstrated strong conceptual and functional knowledge of the Reference Data domain with the ability to apply expertise to complex business scenarios and operational challenges.

Experience in issue resolution, Root Cause Analysis (RCA), process improvement, and operational excellence initiatives.

Good understanding of business drivers and the impact of Reference Data processes on downstream consumers Strong analytical, problem-solving, stakeholder management, and communication skills.

Excellent communication and presentation skills with the ability to clearly explain factual, complex, and dynamic information to stakeholders across various levels.

Proficiency in Generative AI tools such as Microsoft Copilot, NIP, or similar AI platforms .

Experience in data analysis, reporting, automation, and digital transformation initiatives.

Ability to develop SOPs, training materials, and knowledge management frameworks.

Strong focus on data quality, compliance, risk management, and customer satisfaction.

Deep understanding of Data Quality principles, quality controls, governance standards, root-cause analysis, quality metrics, and key drivers impacting quality outcomes across the Reference Data lifecycle.