資深數據分析師 Senior Data Analyst(TVBS Data Team)

Job Summary

The TVBS Data Team is dedicated to building and maintaining high-quality data service platforms. We are seeking a highly skilled and experienced Senior Fullstack Engineer to join our innovative team.

We are looking for a fullstack professional with a strong backend development background (primarily PHP, with Python maintenance skills as a plus), proficient in SQL databases, modern frontend frameworks, and DevOps practices. In this role, you will play a crucial part in architecting systems, leading technical decisions, and solving complex challenges alongside our team.

Key Responsibilities

System Development & Maintenance

• Lead the design, development, and maintenance of backend services, primarily using PHP with Python maintenance capabilities.
• Design and optimize SQL database (MySQL/PostgreSQL).
• Design, develop, and implement robust RESTful APIs to ensure seamless data flow between frontend and backend.
• Develop frontend functionalities using modern JavaScript frameworks (e.g., Vue.js, React, Angular).
• Continuously refactor codebase, write comprehensive technical documentation, and enhance system maintainability.
• Implement caching mechanisms (e.g., Redis) and performance tuning strategies to improve system responsiveness and scalability.
• Improve test coverage to ensure system reliability and stability.

Automation & System Optimization

• Ensure the security, efficiency, and high availability of service environments.
• Leverage Docker and Linux to optimize system performance and streamline development workflows.
• Monitor system performance, proactively identify and troubleshoot issues to maintain high availability and stability.
• Support CI/CD pipeline establishment, automating deployment and testing processes.

Infrastructure & Cloud Management

• Manage and optimize infrastructure to enhance service stability and scalability.
• Operate public cloud platforms (GCP/AWS) for IaaS deployment and operations.
• Utilize Infrastructure as Code (IaC) for environment setup and management.
• Proficiently use Linux command-line tools for operations and troubleshooting.

Technical R&D & Team Collaboration

• Evaluate and experiment with new technologies to drive the evolution of the team's tech stack.
• Actively participate in code reviews to ensure code quality and best practices.
• Collaborate effectively with team members, UI/UX designers, and cross-functional partners to achieve common goals.

Required Qualifications

• 5+ years of experience in data analysis or business analytics (media, advertising, or internet product background is a plus).
• Proficiency in SQL, with the ability to perform complex queries and optimize performance in large-scale data environments (e.g., Data Warehouses, BigQuery).
• Excellent written and verbal communication skills, capable of translating complex data insights and technical constraints clearly to diverse stakeholders and influencing decision-making with data.
• Familiarity with at least one data visualization or BI tool (e.g., Looker Studio, Tableau, Power BI), with the ability to create compelling dashboards and tell stories with data.
• Solid understanding of data modeling concepts, capable of collaborating with data engineers to design analytical models (e.g., Star Schema, denormalized tables for analysis, event data models) and proposing appropriate field and granularity planning based on business and metric requirements.
• Experience with Web/App behavioral data analysis (e.g., GA4, Firebase, or similar tools).
• Strong foundational knowledge of statistics (e.g., hypothesis testing, regression analysis, sample size estimation, A/B testing principles).
• Ability to independently decompose problems and apply structured thinking, translating business challenges into analytical questions.
• Proficiency in reading English technical documentation (e.g., technical papers, API documentation, tool manuals).

Preferred Qualifications

• Especially welcome are data analysts familiar with ad monetization and growth experiments, capable of identifying practical and actionable optimal solutions across content, traffic, and revenue goals.
• Experience with Python for data cleaning, analysis, or automating workflows.
• Practical experience in building recommendation systems, user segmentation (e.g., RFM), LTV prediction, or similar models.
• Familiarity with event tracking planning, tag management tools (e.g., GTM), or practical experience with CDP/DMP platforms.
• Experience collaborating with engineers on data architecture design, defining event schemas, and field naming conventions.
• Familiarity with statistical modeling and basic machine learning concepts, with experience implementing simple models for business applications.
• Experience with ETL/ELT processes (e.g., Airflow, dbt, Dataform).
• Experience analyzing behavioral data for high-traffic websites or large-scale applications.
• Experience with ad campaign performance analysis (e.g., Meta, Google Ads, LAP) or attribution modeling.
• Direct involvement in the planning and implementation of data products or internal data tools, familiar with the complete product lifecycle from requirements definition, design, development, launch, to continuous iteration.