AVP, Data Engineering, Chief Data Office

4 days ago


Tin Shui Wai, Hong Kong SAR China HKEX Technology (Shenzhen) Limited Full time

Lead a data transformation team of 6–8 engineers, fostering delivery excellence and technical leadership Collaborate with analysts and business stakeholders to gather requirements and deliver reliable data solutions Design, build, and maintain scalable data pipelines using SparkSQL and Python Manage and optimize data storage and retrieval within Hadoop Distributed File System (HDFS) Utilize Trino for distributed SQL querying and business intelligence support Ensure data quality, integrity, and security across all systems Monitor and optimize pipeline performance and query execution, conduct performance tuning and profiling Troubleshoot and resolve data-related issues to minimize business impact Manage production incidents and coordinate with the SRE Lead for incident investigation and postmortem analysis Key Responsibilities Drive technical excellence and delivery within the data engineering team Architect and implement robust ETL pipelines and data models Support business intelligence and reporting through efficient data access and transformation Ensure operational reliability and collaborate on incident response Requirements Mandatory Skills and Qualifications Minimum 8 years of experience in data engineering, including 3+ years in a leadership role Strong expertise in SparkSQL for large-scale data processing Proven hands-on experience with HDFS for distributed data management Deep understanding of Trino for distributed SQL execution Proficiency in Python for scripting, automation, and data manipulation Solid grasp of ETL architecture, data modeling, and pipeline design Familiarity with distributed computing principles and big data ecosystems Basic proficiency in English and Mandarin (written and verbal) Preferred Skills Experience with Tableau for data visualization and dashboard development Exposure to cloud platforms such as AWS or Huawei HCS Knowledge of SQL performance tuning and query optimization techniques Background in data governance, data quality, or metadata management Experience with capital markets, trading systems, or investment workflows #J-18808-Ljbffr


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