Data Platform Manager

Our client is a well-established global enterprise with a strong presence across Asia-Pacific and international markets. They operate large-scale, mission-critical operations and are investing heavily in data, analytics, and digital transformation to drive business performance and innovation. As part of this journey, they are expanding their data capabilities and seeking an experienced Data Platform Manager to lead the evolution of their enterprise data platform.

The Data Platform Manager will be responsible for driving the design, development, governance, and operational excellence of the organization's central data platform. This role will lead both local and offshore data engineering teams while partnering closely with business stakeholders, analytics teams, and technology functions to deliver scalable, secure, and high-performing data solutions. The successful candidate will play a key role in shaping data architecture, enabling advanced analytics and AI initiatives, and ensuring data-driven insights translate into measurable business outcomes across the organization.

Key Responsibilities

• Lead the design, implementation, and continuous enhancement of the enterprise data platform architecture, ensuring scalability, security, and alignment with business objectives.
• Manage the development, deployment, and maintenance of data pipelines and integration frameworks using Microsoft Azure technologies, including Azure Data Factory and Azure Databricks.
• Define and enforce enterprise data architecture standards, frameworks, and best practices across the organization.
• Develop and maintain robust data models, integration solutions, and technical designs to support analytics, reporting, AI, and machine learning initiatives.
• Establish and enhance data governance practices, including data quality monitoring, metadata management, data lineage, privacy controls, and regulatory compliance.
• Partner with business teams, data analysts, and technology stakeholders to gather requirements and translate business needs into scalable technical solutions.
• Conduct architecture reviews and ensure all solutions adhere to security, performance, risk, and operational standards.
• Drive adoption of automation, DevOps practices, and cloud-native technologies to improve platform efficiency and reliability.
• Lead incident management, root cause analysis, and remediation planning for critical platform and data-related issues.
• Develop technical documentation, standards, and training materials to promote knowledge sharing and platform adoption.
• Monitor platform performance, resource utilization, and cloud costs, providing recommendations for ongoing optimization and operational improvement.
• Manage and mentor onshore and offshore data engineering teams, fostering a culture of collaboration, accountability, and continuous improvement.

Required Skills and Experience

• Bachelor's Degree in Computer Science, Information Systems, Software Engineering, or a related discipline.
• At least 8 years of experience in Data Engineering, Data Platform Management, Data Architecture, or related disciplines within enterprise-scale environments.

• Proven experience designing and delivering modern cloud-based data platforms and enterprise data solutions.
• Strong knowledge of data architecture principles, scalable design patterns, and data governance frameworks.
• Extensive experience with:
• Azure Databricks
• Azure Data Factory (ADF)
• Azure Data Lake Storage Gen2
• Azure Logic Apps
• Hands-on experience with real-time and streaming data technologies, including:
• Apache Kafka
• Apache Flink
• Change Data Capture (CDC)
• Strong expertise in data modeling, ETL/ELT development, and enterprise data integration.
• Experience supporting advanced analytics, AI, and machine learning workloads.
• Strong understanding of Agile delivery methodologies and DevOps practices.
• Proven track record managing complex data platform environments, troubleshooting critical issues, and driving continuous platform improvements.
• Experience working with geographically distributed teams and stakeholders.
• Relevant Microsoft certifications such as Azure Data Engineer Associate or other cloud data engineering certifications would be advantageous
• Strong communication and stakeholder management skills.
• Fluency in English and Cantonese is required; Mandarin proficiency would be an advantage.