Data Platform Manager

Position Description

The Data Platform Manager is responsible for designing, building, and maintaining the HAECO Central Data Platform by establishing a robust data architecture framework, standards, and best practices. This role leads both onshore and offshore data engineering teams and collaborates closely with the data analytics team, all HAECO business units, and cross-functional partners within Group Digital and Group IT. The Data Platform Manager drives the continuous development and operational excellence of the Central Data Platform, champions data analytics initiatives and data products development, and ensures that data-driven insights translate into measurable strategic business value for HAECO.

What You'll Do

• Lead the end-to-end design, implementation, and continuous enhancement of the central data platform architecture, ensuring alignment with both business objectives and compliance mandates across all data source locations.
• Direct and oversee the development, deployment, and maintenance of data pipelines and processing frameworks on Azure Data Factory and Azure Databricks, guaranteeing performance, scalability, and reliability across onshore and offshore teams.
• Author, refine, and validate comprehensive data models and integration pipelines; oversee model reviews with cross-functional stakeholders to ensure business needs are fully translated into technical solutions.
• Administer and improve data governance, including setting up automated data quality monitoring, metadata management, data lineage tracking, and enforcing privacy-by-design with focus on regulatory compliance.
• Act as primary liaison between business units, analytics, and data engineering teams, facilitating requirements gathering, solution design workshops, and ongoing feedback cycles.
• Arrange and lead regular architectural reviews, ensuring all new designs conform to security, quality, and efficiency standards and enabling early identification of technical risk.
• Champion and coordinate the adoption of automation, DevOps, and new cloud-native technologies; run proof-of-concepts and production pilots.
• Lead incident management and root cause analysis for platform or data issues. Develop and enforce remediation and prevention plans in collaboration with security and compliance functions.
• Define, communicate, and enforce best practices through documentation, onboarding, and regular training sessions, fostering a shared culture of accountability, innovation, and technical excellence across all team members.
• Regularly monitor performance metrics, resource utilization, and cost trends; report findings and recommend actions to both business and IT leadership for continuous optimization.

What You'll Need

1. Functional and other Relevant Experience

• At least 8 years of experience in enterprise data engineering, data platform management, data architecture, data governance, and end-to-end data solution delivery within modern cloud environments.
• Proven expertise in developing, optimizing, and maintaining data architectures, leveraging modular, scalable, and cloud-native design patterns for high-availability and security.​
• Advanced skills in data modeling, integration techniques, and implementation of industry-standard frameworks to support advanced analytics, AI, and machine learning workloads.​
• Hands-on proficiency with real-time data processing technologies such as Apache Flink, Change Data Capture (CDC), Kafka, alongside deep expertise in Microsoft Azure data ecosystem components including Azure Databricks, Azure Data Factory, Azure Data Lake Gen2, and Logic Apps, focusing on orchestration, automation, and streaming data workflows.
• Strong experience applying agile and DevOps methodologies to coordinate multi-disciplinary teams and ensure rapid, iterative platform improvements.
• Demonstrated capability for diagnosing, troubleshooting, and performing root cause analysis on complex enterprise data systems and processes, leading to effective resolution and platform resilience.​
• Previous involvement with aviation data or operations is valued.

2. Qualifications and other Relevant Knowledge

• Bachelor’s degree in Computer Science, Information Systems, Software Engineering, or related disciplines.
• Certifications in data engineering disciplines from leading vendors, such as Databricks Certified Data Engineer and Microsoft Certified: Azure Data Engineer Associate, is an advantage.
• Fluent in English, Mandarin is an advantage.