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.
Full-time