Data Architect - Assistant Vice President - Chief Data Office - IT
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Full-time
bachelor degree
Posted 30d ago
~40 hrs/week
Responsibilities
The Data Architect is responsible for designing scalable data models and frameworks for the enterprise data warehouse to support AI and analytics. This includes managing metadata, improving ETL pipelines, and collaborating across teams to ensure data quality and governance.
Requirements
Requires a Bachelor's degree in Computer Science or a related field with over 5 years of experience in data engineering and architecture, specifically within the financial services industry. Candidates must have hands-on experience with data modeling tools, SQL, and a foundational understanding of cloud data warehouses and AI applications.
Full job description
Company Introduction:
We’re home to Asia's most dynamic and vibrant capital markets. Connecting capital, ideas, inspiration and innovation for deeper, more diverse and liquid global capital markets; providing greater choice and opportunity for our customers, each and every day.
HKEX is a purpose-driven company. Our commitment to the long-term development of our business and our markets is articulated in our purpose: "To Connect, Promote and Progress our Markets and the Communities they support for the prosperity of all."
Job Summary:
Data Architect supports Chief Data Office by building a scalable, well structured, and AI ready data foundation. As HKEX expands its data warehouse, modernizes platforms, and increases the use of analytics and AI, this role ensures that data is organized, governed, and modeled effectively. The incumbent will work closely with senior architect and data engineers to improves data quality, accessibility, and efficiency across systems, enabling better decision making and smoother adoption of emerging technologies.
Job Duties:
Job Responsibilities:
Data Architecture & Modeling
Design conceptual, logical, and physical data models for the enterprise data warehouse and data marts.
Participate in defining data standards, modeling conventions, and reusable data patterns.
Support dataset design for analytics, BI, and machine‑learning workloads.
Data Platform & Ecosystem
Design frameworks for metadata management, data governance, lineage tracking, and asset cataloging.
Support configuration of data quality rules and workflows.
Managing modeling and documentation activities within the Data Platform environment.
Data Mining, Machine Learning & AI for Data Warehouse
Apply basic data mining techniques (profiling, clustering, outlier detection) to better understand source data and inform data model design.
Use machine learning fundamentals to identify opportunities for optimization (e.g., workload prediction, query pattern analysis, intelligent partitioning).
Support the application of AI in the data warehouse, such as:
Automated metadata classification
AI‑driven data quality rule recommendations
Pattern detection for schema improvements
Automating ETL logic generation
Collaborate with data analysts to ensure warehouse structures support ML pipelines and feature stores.
ETL / Data Pipeline Development
Provide architecture consultancy on improving ETL/ELT pipelines developments quality and efficiency.
Design data flows between on‑premises systems, cloud storage, and the data warehouse.
Contribute idea to improving pipeline reliability and monitoring.
Cloud Data Warehouse Support
Manage data warehouse cloud migration tasks such as mapping, validation, and reconciliation.
Support POCs for cloud-based architectures, storage layers, and compute services.
Develop and apply best practices for scalable, secure cloud DW architecture.
Cross‑Team Collaboration & Governance
Work with data engineers, analysts, and business teams to deliver data requirements.
Support governance processes such as data lineage, catalog updates, and access reviews.
Document technical designs, data dictionaries, and operational procedures.
Job Requirements:
Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related field.
5+ years of experience in data engineering and architecture, particularly within the FSI sector.
Understanding of data architecture principles (data layers, integration patterns, schema design).
Hands‑on experience with data modeling tools.
A fast learner with understanding of data technology a preference.
Experience with ETL/ELT development and SQL transformation logic.
Foundational exposure to cloud data warehouses
Basic understanding of Visualization tools, Data mining methods (profiling, segmentation, correlation analysis), Machine learning concepts (supervised vs. unsupervised learning, model lifecycle), AI applications in data management (metadata extraction, classification, automation)
HKEX is committed as an Equal Opportunity Employer. Diversity is one of our core values and we look to support, respect diverse perspectives, abilities, culture and experiences within our workplace.
Location:
HK-DTH 9/F
Shift:
Standard - 40 Hours (Hong Kong SAR)
Scheduled Weekly Hours:
40
Worker Type:
Permanent
Related keywords
Data ArchitectureData ModelingEnterprise Data WarehouseData MartsMetadata ManagementData GovernanceData LineageAsset CatalogingData MiningMachine LearningAIETLELTCloud MigrationSQLFSI
About Hong Kong Exchanges and Clearing Limited (HKEX)
HKEX Group is a global exchange group, operating dynamic and integrated financial markets in Asia and Europe.
From our home in the financial hub of Hong Kong and an additional base in London, we provide world-class facilities for trading and clearing securities and derivatives in Equities, Commodities, Fixed Income and Currency.
Uniquely positioned at the intersection of Chinese and international capital flows, Hong Kong has long been Connecting China with the World. With the accelerated opening-up of China’s capital markets, HKEX continues to be at the forefront of this historic transition, which we believe will Shape the Global Market Landscape.
Offices: 8/F, Two Exchange Square,, 8 Connaught Place, Central,, Hong Kong, Hong Kong 000000, HK