Our client is a global firm and they are seeking a Data Platform Leader to shape the future of its enterprise data capabilities. This role sits at the intersection of technology strategy and business enablement, driving how data flows, transforms, and delivers value across a complex, multi-site operation. You’ll own the technical vision and execution for a centralized data infrastructure that supports advanced analytics, operational intelligence, and emerging AI/ML initiatives. Working with a blend of onshore and offshore engineering talent, you’ll build scalable, governed, and high-performance data solutions that directly influence how the business operates and competes. Key Responsibilities Lead the architecture, development, and continuous evolution of the enterprise data platform, defining technical standards and ensuring infrastructure scales to meet analytical and operational demands Design and oversee data pipelines, processing frameworks, and integration patterns that connect diverse source systems into a coherent, reliable data ecosystem Manage and develop a distributed engineering team across multiple locations, setting direction, coaching talent, and fostering a culture of technical excellence and continuous improvement Serve as the primary liaison between technical teams and business stakeholders, translating requirements into solutions through workshops, design reviews, and ongoing collaboration with analytics teams, business units, and IT partners Establish and enforce data governance frameworks covering data quality, metadata management, lineage tracking, and privacy compliance to ensure data remains trustworthy and well-documented Champion modern engineering practices including automation, DevOps, and cloud-native approaches, running proof‑of‑concepts and driving adoption of emerging technologies Lead incident response and root cause analysis when platform or data issues arise, developing remediation plans and strengthening system resilience in partnership with security and compliance functions Monitor performance metrics, cost trends, and resource utilization, providing insights and recommendations to leadership for ongoing optimization Role Requirements: Experience & Background Minimum 8 years of progressive experience in data engineering, platform architecture, or data management within enterprise environments Proven track record of designing and delivering data solutions at scale, ideally within organizations operating across multiple sites or business units Experience with cloud-native data architectures, modern lakehouse patterns, and building for high availability and security Exposure to aviation, aerospace, logistics, or similarly complex operational industries is a plus but not required Technical Expertise Deep proficiency in the Microsoft Azure data ecosystem, with hands‑on experience across Databricks, Data Factory, Data Lake Storage, and related orchestration and automation tools Strong experience with real‑time data processing, streaming technologies, event‑driven architectures, and change data capture mechanisms such as Kafka or Flink Advanced skills in data modeling, integration techniques, and implementing frameworks that support advanced analytics and machine learning workloads Practical experience implementing data governance including automated quality checks, metadata catalogs, lineage documentation, and privacy‑by‑design approaches Familiarity with agile and DevOps methodologies to coordinate multi‑disciplinary teams and drive rapid, iterative platform improvements Experience leading engineering teams, ideally across geographies or in hybrid onshore/offshore delivery models Strong stakeholder engagement skills with the ability to facilitate workshops, lead architecture reviews, and communicate complex concepts to both technical and business audiences Structured approach to problem‑solving with demonstrated capability in diagnosing issues, performing root cause analysis, and driving sustainable resolutions Education & Credentials Bachelor's degree in Computer Science, Information Systems, Software Engineering, or a related discipline Relevant certifications in data engineering from Databricks or Microsoft are valued but not mandatory if hands‑on expertise is clearly demonstrated Language Fluency in English is required Mandarin proficiency is advantageous #J-18808-Ljbffr
