Our client is seeking a strategic and technically strong Data Platform Manager to lead the evolution of their enterprise data platform. This role is responsible for architecting, scaling, and optimizing the central data ecosystem, ensuring that high‑quality, compliant, and actionable data is available to drive analytics, AI, and business decision‑making across the organisation.
Key Responsibilities
- Lead the end‑to‑end design, implementation, and continuous enhancement of the enterprise data platform, ensuring alignment with business needs, data governance standards, and regulatory requirements.
- Oversee the development and optimization of data pipelines and processing frameworks built on Azure Data Factory and Azure Databricks, ensuring performance, reliability, and scalability across both onshore and offshore teams.
- Define, refine, and validate enterprise data models and integration pipelines, ensuring business requirements are accurately translated into robust technical solutions.
- Drive data governance practices, including automated data quality monitoring, metadata management, lineage tracking, and privacy‑by‑design principles.
- Act as a key liaison between business stakeholders, data engineering, and analytics teams to streamline requirements gathering, solution design, and delivery.
- Lead architectural reviews to ensure new solutions meet security, performance, and efficiency standards, while proactively identifying technical risks.
- Champion automation, DevOps, and new cloud‑native technologies; lead proof‑of‑concepts and production pilots to enhance platform capabilities.
- Oversee incident management and root‑cause analysis for platform or data issues, ensuring effective remediation and continuous improvement.
- Establish and maintain best practices through documentation, onboarding, training, and knowledge‑sharing to promote a culture of quality and innovation.
- Monitor platform performance, cost, and resource utilisation; provide insights and recommendations to business and IT leadership for ongoing optimisation.
Key Requirements
- Bachelor's degree in Computer Science, Information Systems, Software Engineering, or related discipline.
- Minimum 8 years of experience in enterprise data engineering, data platform management, data architecture, or data governance within modern cloud environments.
- Proven ability to design, build, and maintain scalable and secure data architectures supporting advanced analytics, AI, and machine learning workloads.
- Strong expertise in data modelling, integration design patterns, and cloud‑native data engineering frameworks.
- Hands‑on experience with Azure technologies, including Databricks, Data Factory, Data Lake Gen2, Logic Apps, and orchestration/automation frameworks.
- Familiarity with real‑time and streaming technologies such as Kafka, CDC frameworks, or Apache Flink is a strong advantage.
- Skilled in diagnosing complex platform or data pipeline issues and performing root‑cause analysis in large‑scale enterprise environments.
- Experience working with agile and DevOps methodologies to drive iterative delivery across multidisciplinary engineering teams.
- Professional certifications such as Microsoft Certified: Azure Data Engineer Associate or Databricks Certified Data Engineer are preferred.
Our client offers competitive compensation and benefits, as well as a dynamic and fast-paced work environment.
Interested parties, please send your CV to Ron Lee on Ron.Lee@connectedgroup.com or contact on +852 39725817 for more details. For other available opportunities, please visit www.connectedgroup.com
