Data Director
7 days ago
I. Job Overview
The Data Director is responsible for developing and driving the company's overall data strategy and data governance system. Through data platforms, analytical models, and data products, they support the company's strategic decision-making, business growth, operational optimization, and risk management. This role involves being both a business strategy partner and the person in charge of building data capabilities, ultimately bearing responsibility for maximizing the value of the company's data assets.
II. Key Responsibilities
- Data Strategy and Governance
Develop the company's medium- and long-term data strategy, data roadmap, and implementation plan.
Establish and continuously optimize the data governance system (data standards, definitions, master data, lineage, quality, permissions).
Lead data asset inventory and promote data assetization and data value assessment.
Ensure data compliance (e.g., GDPR, cross-border data transfer, privacy protection, etc.).
- Data Platform and Technical Architecture
Responsible for the construction of enterprise-level data platforms (data warehouse / data lake / lakehouse).
Guide the design of data collection, integration, modeling, computing, and storage architecture.
Promote the construction of BI, self-service analytics, indicator systems, and data visualization.
Evaluate and introduce appropriate data tools, cloud platforms, and third-party solutions.
- Business Analysis and Decision Support
Transform business problems into data models and analytical frameworks.
Support the Board of Directors and senior management (CEO / CFO / ... COO's Key Decision Analysis
Build an operational analysis system (e.g., revenue, cost, cash flow, ROIC, EBITDA)
Drive the deep application of data in sales, operations, supply chain, finance, and post-investment management
- Data Products and Advanced Analytics
Promote data productization (indicator dashboards, predictive models, early warning systems)
Guide advanced analytics and modeling (prediction, optimization, scenario analysis)
Explore the practical application of AI/machine learning in business
Support core business scenarios such as pricing strategies, customer segmentation, and demand forecasting
- Team Building and Cross-Departmental Collaboration
Build and manage a data team (data engineering, data analytics, data science, BI)
Establish data talent development, performance, and incentive mechanisms
Work closely with IT, finance, business departments, and external consultants
Enhance the organization's overall data literacy
III. Key Deliverables (Deliverables)
Enterprise-level data strategy and annual data planning
Unified core indicator system and business analysis model
Highly available, high-quality data platform and analysis system
Data insight reports supporting senior management decision-making
Sustainable iterative data governance and operation mechanism
IV. Qualifications
- Education and Background
Bachelor's degree or above in Computer Science, Statistics, Mathematics, Information Systems, Economics, or a related field
Over 20 years of experience in data, BI, analytics, or IT-related fields
At least 5 years of experience in data team management or as a data lead
