Senior Vice President of Data

Job Description: Senior Vice President of Data

The Senior Vice President of Data is a key executive responsible for the company's data strategy and data assets. Typically reporting directly to the CEO or CTO, this role drives enterprise growth through data, optimizes decision-making frameworks, and builds scalable data platforms and governance systems. I. Core Responsibilities

1. Data Strategy and Vision Formulation

• Formulate the company's overall data strategy, ensuring alignment with business growth objectives
• Drive the evolution of data from a "support tool" to a "core productive force and strategic asset"
• Foster a data-driven culture

2. Data Platform and Architecture Construction

• Oversee the overall architectural design of data platforms (Data Platform / Data Lake / Data Warehouse)
• Drive the development of real-time data processing, data engineering, and data pipeline (ETL/ELT) systems
• Ensure system high availability, scalability, and security

3. Data Governance and Compliance

• Establish a data governance framework
• Ensure data quality, consistency, and standardization
• Manage data privacy and compliance (e.g., GDPR, CCPA)

4. Data Analysis and Business Insights

• Lead data science and analytics teams to provide business insights
• Build a metrics framework (KPIs / North Star Metrics)
• Drive the development of predictive models, user behavior analysis, and growth models

5. AI and Data Intelligence

• Drive the implementation of AI/machine learning in business operations (recommendation systems, risk control, intelligent operations, etc.)
• Establish MLOps systems to facilitate model engineering and large-scale application

6. Team Management and Organizational Development

• Build and manage teams across data engineering, data science, data analytics, and data governance
• Define talent development paths and organizational structure optimization plans
• Facilitate cross-departmental collaboration (Product, Technology, Marketing, Operations, Finance, etc.)

II. Qualifications

Education

Bachelor’s degree or higher in Computer Science, Statistics, Mathematics, Engineering, or a related field (Master’s/PhD preferred)

Experience

• 20+ years of data-related experience, including 5+ years in senior management
• Experience building data platforms for large-scale internet, fintech, AI, or multinational enterprises
• Experience building data systems from scratch (0-to-1) is preferred

Technical Skills

• Proficiency in big data technology stacks (Hadoop, Spark, Kafka, Flink, etc.)
• Familiarity with cloud platforms (AWS / GCP / Azure)
• Competence in data modeling and data warehouse design
• Understanding of machine learning and AI application scenarios

Business Acumen

• Ability to translate data into business growth strategies
• Strong capability in data-driven decision-making (Growth / Revenue / ...) Leadership

• Strong cross-functional communication and strategic execution capabilities
• Ability to lead technical teams of over 100 people
• Experience in managing global organizations preferred