Data Analyst (Finance)

About the Team:

You will be part of Sea’s HQ Finance department, which plays an integral role in supporting the accounting and finance needs of our three core businesses (Garena, Shopee, Monee) and across our diverse regional market presence. Within the department, the Group Data function builds and maintains scalable data infrastructure through data ingestion, transformation, and warehousing via robust ETL pipelines, while also developing web-based tools that enable efficient access and interaction with data systems to support accurate reporting and analysis.. You will play an important role in delivering high quality and comprehensive analysis to support the respective business needs. Besides applying your strong technical knowledge in our projects, you will be involved in designing and implementing innovative elements to meet the needs of our growing business.

Job Description:

As a Data Analyst, you will play an important role in delivering high quality and comprehensive analysis to support the respective business needs. Besides applying your strong technical knowledge in our projects, you will be involved in designing and implementing innovative elements to meet the needs of our growing business

• Understand user requirements; Design data deliverables
• Understand data source; Design data warehouse and ETL pipelines
• Develop, deliver and maintain ETL pipelines using various technologies
• Manage data, scripts and documentation according to compliance rules
• Help users with offline data processing and raise their efficiency by automating routine jobs
• Collaborate with data platform team and strive for better platform features to ease ETL development
  
  
  

Requirements:

• Bachelor's degree or higher in computer science, business analytics, mathematics, statistics or related disciplines.
• Self-learner with a strong sense of ownership.
• Deep understanding of SQL and Python are required; Experience in other programming languages, such as R, Scala, Java and Shell is preferred.
• Hands-on experience on big data technology, such as Hadoop, Spark and Flink is preferred.
• Strong analytical skill, strong verbal and written communication skills.