Description

Key Responsibilities

Data Operations & Incident Management

• Lead and coordinate the end-to-end incident management lifecycle for data-related production issues.
• Drive timely incident resolution, root cause analysis (RCA), and preventive action planning.
• Act as the primary escalation point for critical and high-priority BAU incidents.
• Monitor data pipelines, interfaces, ETL/ELT processes, data quality issues, and platform performance.
• Ensure compliance with SLA, KPI, and operational governance requirements
• Coordinate workload planning, resource allocation, and on-call support activities.

Stakeholder Management & Communication

• Collaborate closely with Data Custodians, Business Users, Application Support Teams, and Vendors to troubleshoot and resolve data issues.
• Liaise with business users to understand impacts, prioritize remediation activities, and provide timely status updates.
• Prepare executive-level communications and provide concise updates to senior management during major incidents.
• Facilitate incident review meetings, service review discussions, and governance forums.

Data Migration & Project Delivery

• Lead and support data migration projects involving data extraction, transformation, validation, reconciliation, and cutover activities.
• Coordinate with business, technology, and vendor teams to ensure successful project execution.
• Develop migration strategies, implementation plans, rollback procedures, and testing approaches.
• Oversee data validation and reconciliation activities to ensure data integrity during migrations.

Data Governance & Quality Management

• Support data governance initiatives and ensure adherence to enterprise data standards.
• Work with data owners and data custodians to improve data quality, lineage, and stewardship processes.
• Implement controls and monitoring mechanisms to identify and prevent recurring data issues.
• Maintain operational documentation, runbooks, support procedures, and knowledge repositories.
• Identify recurring issues and drive automation opportunities to reduce manual effort and improve reliability.

Job Requirements

• Bachelor's Degree or above in Computer Science, Information Technology, Data Engineering, Data Science, Business Analytics, or a related discipline.
• Minimum 8+ years of experience in Data Engineering, Data Operations, Production Support, Data Warehousing, or Enterprise Data Management.
• Strong analytical, problem-solving, and decision-making skills.
• Proven experience managing mission-critical production supports environments and leading end-to-end incident management processes.
• Demonstrated experience in leading data migration, data transformation, and enterprise data integration initiatives.
• Experience managing teams of Data Custodians, Data Analysts, Data Support Engineers, or related functions.
• Strong stakeholder management experience, including engagement with senior business leaders and executive management.
• Experience working in Retail, Consumer Goods, Fashion, Luxury Retail is highly preferred.
• Understanding of retail KPIs, customer data platforms (CDP), loyalty programs, omnichannel customer journeys, and store operations data is highly desirable.
• Experience supporting regional or global data platforms across multiple Asia-Pacific markets is advantageous.
• Fluency in both English and Mandarin/Cantonese (written and spoken)
• Proficiency in Korean is highly desirable.

Technical Skills

• Strong SQL and database troubleshooting skills.
• Hands-on experience with enterprise data platforms and cloud data technologies.
• Experience with ETL/ELT tools and data integration frameworks.
• Knowledge of data governance, metadata management, and data quality frameworks.
• Experience with Salesforce, Salesforce Marketing Cloud or Heroku platforms.
• Familiarity with Azure, AWS, Databricks, Snowflake, Synapse, or Google Cloud Platform.
• Experience using ServiceNow, Jira, Azure DevOps, or similar ITSM platforms.