Data Warehouse Engineer Graduate (Data Platform, Global E-Commerce) - 2027 Start
TikTok
- Location
- Singapore, Singapore, Singapore
- Employment
- Full Time
- Work model
- On-Site
- Level
- New Grad
- H-1B history
- 148 approvals (FY2023)
Skills
About this role
Team Introduction Our Data Platform Business Partnering team is at the core of TikTok E-Commerce business, responsible for generating tremendous amount of data and providing accessing services and applications. We empower many business & engineering teams to analyze and develop innovative strategies and products driving business growth. We are looking for passionate and talented engineers to join us to drive the future of E-Commerce together.
We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities - Translate business requirements and end-to-end solution designs into technical implementations, and build batch and real-time data warehouses. - Lead data modeling design, and develop, maintain, and optimize ETL jobs. - Collaborate with business teams to define and build data metrics based on the data warehouse. - Build and maintain data products that support business analysis and decision-making. - Participate in system rollouts, upgrades, implementations, and releases to streamline internal processes and improve operational efficiency. - Develop and implement analytical techniques and data applications to transform raw data into meaningful insights using data-oriented programming languages and visualization tools. - Apply data mining, data modeling, natural language processing, and machine learning techniques to extract and analyze information from large-scale structured and unstructured datasets. - Visualize, interpret, and communicate data findings, including the creation of dynamic reports and dashboards.