Head of Data Platform (Open for Expat)

ACG3169JOB

Our client is a leading financial services company in Vietnam who is looking for experienced talent to join their firm.

Leadership and Strategy

• Strategic Roadmap: Develop and execute the strategic roadmap for the Data Platform Center ensuring deep alignment with the organizations overarching data and IT strategies.
  

• Architecture Direction: Drive the design and implementation of enterprise data architecture to effectively support Company-wide data systems.
  

• Functional Oversight: Provide executive leadership across all functional areas of the center including Data Product Data Engineering Data Architecture and Change Request (CR) Management.
  

• Stakeholder Liaison: Serve as the key liaison between business units IT teams and data stakeholders to ensure strategic alignment and maximize value delivery from data initiatives.
  

• Cultural Excellence: Champion a culture of innovation operational excellence and continuous improvement within the center.
  

Enterprise Data Architecture

• Governance & Principles: Lead the design and governance of enterprise-wide data architecture principles frameworks and core concepts.
  

• System Alignment: Oversee the alignment of system design and interoperability to ensure consistency and seamless integration across all data systems.
  

• Strategic Collaboration: Collaborate with IT architects to deliver integrated enterprise data and IT strategies.
  

Data Product Management

• Business Requirements & CR Development: Manage the translation of business requirements and the subsequent development of change requests (CRs) related to the Data Warehouse and associated data products.
  

• Compliance Reporting: Oversee the design and delivery of data pipelines and reporting systems to comply with relevant regulatory requirements (e.g. Central Bank circulars).
  

• Innovation & Strategy Alignment: Drive cloud and other data product initiatives ensuring alignment with the broader Enterprise Data Analytics (EDA) strategy.
  

Data Engineering and Operations

• Pipeline Management: Oversee the design implementation and maintenance of end-to-end data pipelines and data processing systems across the enterprise data zone (Data Warehouse).
  

• Data Integration: Manage the integration of raw data into downstream systems to serve multiple business units (for analytics AI/ML and application/system needs).
  

• Operational Stability: Ensure the stability scalability and cost-effectiveness of data provisioning systems and day-to-day operations including rigorous SLA management data observability and effective issue resolution.
  

• Security & Support: Lead infrastructure application support and security fixes for systems managed by the Data Platform Center.
  

Change Request (CR) Management

• Quality Assurance: Ensure the delivery of Change Requests (CRs) meets agreed-upon timelines business requirements and high-quality standards.
  

• Communication & Collaboration: Lead communication and updates with business functions through appropriate forums to ensure transparency and collaborative execution.
  

• Prioritization & Optimization: Oversee CR prioritization resource allocation Service Level Agreement (SLA) management and performance tracking to optimize service delivery.
  

• Process Improvement: Recommend and implement process and technology improvements to enhance efficiency in CR delivery.
  

Team Management and Development

• Team Building: Build and develop a high-performing team across critical functions: Data Product Data Engineering Data Architecture and CR Management.
  

• Performance Benchmarks: Define clear roles responsibilities and performance benchmarks to ensure operational excellence across all teams.
  

• Mentorship & Culture: Mentor and empower team members actively fostering a culture of collaboration innovation and accountability.
  

• Resource Optimization: Manage resources and cost optimization across the center to ensure sustainable and efficient delivery of services.
  

Change Management & Process Improvement

• Change Management Expertise: Proven experience in managing high volumes of change requests effective prioritization and ensuring timely and effective delivery of changes.
  

• Operational Enhancement: Demonstrated track record of implementing process improvements that enhance data pipeline efficiency and reduce operational costs.
  

Working with Business Units & Stakeholders

• Data Requirements Definition: Experience in collaborating closely with diverse business units to define precise data product requirements and ensure data systems effectively support business objectives.
  

• Technology Alignment: Familiarity with aligning IT and business goals through data-driven solutions.
  

Requirements

Educational Qualifications

• Bachelors or Masters degree in Computer Science Engineering Data Science or a related field (Finance Banking Applied Technology etc.).
  

Relevant Knowledge/Expertise

• Experience (Mandatory): Minimum of 10 years of experience in data-related roles with at least 5 years in a leadership position managing teams across data engineering architecture and product functions.
  

• Leadership Experience (Preferred): Experience leading cross-functional teams preferably in large-scale enterprise data environments.
  

• Technical Deep Dive: Expertise in:
  

• Data Architecture and Data Engineering
  

• Data Product Management and Change Request (CR) Management
  

• Cloud Computing & Data Platforms
  

• Security & Compliance BI AI & Machine Learning applications
  

• Industry Best Practices: In-depth knowledge of data management best practices and industry standards including data governance security and data privacy.
  

• Data-Driven Leadership: Experience in leading the implementation of data-driven strategies that deliver tangible business outcomes.
  

• Data Platform Development & Management: Proven track record of overseeing the design implementation and maintenance of enterprise-wide data platforms and solutions.
  

• Cloud Infrastructure: Experience in managing cloud-based data infrastructure and ensuring its alignment with business needs.
  

Key Skills and Competencies

• Leadership & Team Management: Demonstrated strength in leadership team management strategic decision-making project & resource management.
  

• Operational Excellence: Focus on performance monitoring & optimization innovation & continuous improvement.
  

• Functional: Excellent communication & collaboration analytical thinking & problem-solving results-oriented and high accountability.
  

• Technical Proficiency:
  

• Experience with core data technologies (e.g. SQL NoSQL Hadoop Spark) and data platforms (e.g. Snowflake Redshift BigQuery).
  

• Familiarity with AI/ML tools and how data platforms can support data science initiatives.
  

Contact: Huong Do

Due to the immense number of applications only shortlisted candidates will be contacted.