Lead Data Management (Databricks) - Reputed Conglomerate

A reputed conglomerate in Hong Kong seeks a Lead Data Management Professional (Databricks) to build and scale enterprise data platforms, enabling analytics, AI innovation, and data-driven business transformation.

Key responsibilities:

• Own the centralised analytics platform, implementing data governance, security, privacy, and quality controls to ensure compliance, trust, and enterprise-wide data integrity
• Build and maintain scalable data foundations by integrating business, CRM, leasing, and third-party data sources, enabling consistent enterprise intelligence and self-service analytics
• Develop reusable customer data products and privacy-compliant solutions that enhance personalisation, consent management, data quality, and customer insight generation
• Design robust data pipelines and analytics datasets supporting descriptive, diagnostic, predictive, and prescriptive use cases while enabling AI and generative AI initiatives
• Establish scalable DataOps and MLOps capabilities, ensuring platform readiness, operational efficiency, and support for emerging technologies across the organisation
• Drive engineering excellence by defining best practices across coding standards, CI/CD, orchestration, observability, testing, documentation, and Agile delivery frameworks
• Lead internal engineers and external partners while owning platform reliability, stakeholder engagement, SLA performance, incident management, and cost-effective delivery outcomes

Candidate profile:

• Degree in Computer Science, Data Engineering, Information Systems, or a related discipline, with 10+ years' data engineering experience including 3–5 years in a technical leadership capacity
• Hands-on expertise in cloud-based data platforms (preferably Azure) and modern data architectures including data lakes, lakehouses, and data warehouses
• Strong programming and engineering capabilities across SQL, Python, PySpark, and distributed data processing technologies such as Spark and Databricks
• Experience designing and managing data pipelines, orchestration frameworks, CI/CD processes, and DevOps-driven data platform delivery
• Exposure to data governance frameworks and tools, including metadata management, lineage, cataloguing, access controls, and enterprise governance practices
• Strong background in data quality, observability, monitoring, reconciliation, and platform reliability to support trusted analytics and AI outcomes
• Proven ability to translate business requirements into scalable data products while managing stakeholders, vendors, compliance requirements, and cross-functional delivery in customer-centric environments

About the company:

A reputed conglomerate with a strong portfolio of customer-focused assets is advancing digital and data-driven transformation. It offers a collaborative environment where employees can innovate, grow, and shape future business capabilities.

Keywords: data management, Databricks, data analytics, data engineering, AI, DataOps, MLOps, SQL, Python, PySpark

What’s next:

Shape the future of enterprise data and AI by building the platforms that power smarter decisions and lasting business impact. Apply now!