Data Architect

Global Sports Jobs Limited; Hong Kong; On-site; HKD 1,000,000 - 2,000,000; Full time

Benefits offered by this job

Competitive salary

Dynamic working environment

Development opportunities

Job summary

Global Sports Jobs Limited seeks an experienced Enterprise Data Architect to drive our data strategy during a major digital transformation. You will define standards, govern scalable data platforms and lead enterprise data modelling across business, product and technology teams.

You will partner with stakeholders to ensure data contracts align with operational needs while promoting CI/CD, IaC and platform automation for reliable delivery and cost efficiency.

Qualifications

• 8-12 years in data engineering/architecture with enterprise-scale platforms.
• Cloud data platforms design on AWS, Azure or equivalents.
• Expertise in data lake, data warehouse and lakehouse design.
• Experience with Data Vault and dimensional modelling.
• Strong governance, metadata, lineage and security frameworks.
• Knowledge of CI/CD and IaC practices; Terraform/CloudFormation.
• Excellent communication and stakeholder management.

Responsibilities

• Define and maintain enterprise data architecture standards and roadmaps.
• Design and govern scalable data architectures across platforms.
• Lead data modelling for business, operational and analytical use cases.
• Promote data governance, quality, metadata and security practices.
• Collaborate with stakeholders to align models with requirements.
• Provide reviews for data pipelines, APIs and platform enhancements.
• Drive platform scalability, cost optimisation and reliability.
• Evaluate emerging data/AI/cloud capabilities.

Skills

Data modelling

Data architecture

Data governance

CI/CD

DevOps/DataOps

Platform automation

Stakeholder management

Cloud computing

Distributed data processing

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science or related

Tools

AWS

Azure

Terraform

CloudFormation

Data Lake

Data Warehouse

Databricks

ETL tools

Spark

Airflow

Job description

About the Role

The role leads enterprise data architecture for the Club's digital transformation programme, known internally as AOP, which aims to accelerate platform, product, people, performance and potential through innovation and delivery excellence. The position defines and maintains data architecture standards, governs scalable data platforms and leads data modelling across the enterprise. The work spans product, technology, operations, delivery and change, partnering closely with business stakeholders, Product Owners, Data Engineers and downstream application teams. The team is diverse and passionate about solving complex challenges, delivering meaningful impact and creating value for customers, members, the Club and the wider community.

Key Responsibilities

• Define and maintain enterprise data architecture standards, best practices, reference architectures and roadmaps for modern data platforms
• Design and govern scalable data architectures, including data lakes, data warehouses, lakehouse platforms, data integration patterns and analytical solutions
• Lead data modelling activities, including conceptual, logical and physical data models to support business, operational and analytical use cases
• Establish and promote best practices for data governance, data quality, metadata management, lineage, security, privacy and master/reference data management
• Partner with business stakeholders, Product Owners, Data Engineers and downstream application teams to ensure architecture, data models and data contracts align with business and operational requirements
• Provide architecture guidance and design reviews for data pipelines, integrations, APIs, messaging solutions and platform enhancements
• Drive platform scalability, reliability, performance tuning and cloud cost optimisation across databases, data warehouses and data lake environments
• Promote modern engineering practices including CI/CD, Infrastructure-as-Code, automation, observability and platform governance
• Evaluate emerging technologies and provide recommendations on future data, analytics, AI and cloud capabilities

Required Experience & Qualifications

• 8-12 years of experience in data engineering, data architecture or related disciplines, with demonstrated architecture ownership for enterprise-scale platforms
• Strong hands-on experience designing and implementing cloud-based data platforms on AWS, Azure or other major cloud platforms
• Proven expertise in data architecture, data lake, data warehouse and lakehouse design principles
• Strong experience in data modelling, including dimensional modelling, Data Vault and operational data modelling techniques
• Experience establishing and implementing data governance, data quality, metadata management, lineage and security frameworks
• Strong understanding of distributed data processing technologies such as Spark and cloud-native analytics services
• Experience designing highly scalable, resilient and cost-efficient platforms handling large volumes of data
• Practical experience optimising database, data warehouse and data lake performance, storage design, resource utilisation and cloud operating costs
• Strong understanding of CI/CD, DevOps/DataOps practices, Infrastructure-as-Code (Terraform, CloudFormation or equivalent) and platform automation
• Excellent communication and stakeholder management skills, with the ability to influence both technical and business audiences
• Knowledge of enterprise integration patterns, APIs, messaging architectures and data contract design
• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science or a related discipline
• Data processing skills: PySpark, SQL, Spark, Apache Airflow, AWS Glue and Azure Data Factory
• Cloud and infrastructure skills: AWS (S3, Glue, EMR, Redshift, Athena, Lake Formation), Azure (ADLS, Synapse, Databricks, Fabric, Event Hub), Terraform and CloudFormation
• Data architecture and modelling skills: dimensional modelling, Data Vault, lakehouse, data mesh, data fabric and Medallion Architecture

Preferred Skills

• Experience in gaming, entertainment, loyalty, customer analytics or related industries
• Experience with Medallion Architecture, lakehouse, data mesh, data fabric or other modern architectural patterns
• Experience with cloud migration, platform modernisation and hybrid-cloud implementations
• Knowledge of Chinese cloud platforms and ecosystems such as Alibaba Cloud, Tencent Cloud, Huawei Cloud or Volcano Engine
• Exposure to AI/ML, Generative AI, RAG, vector databases, LLM platforms or MLOps architectures
• AI and advanced analytics tooling: Azure OpenAI, Amazon Bedrock, vector databases, RAG, LLM platforms and AI/ML workloads
• AWS, Azure, Databricks, Terraform or other relevant cloud and data platform certifications are advantageous

Benefits & Perks

• Competitive salary and benefits package
• Dynamic working environment
• Development opportunities