Data Quality Assurance Engineer, Data Platform

Found in: Talent SG C2 - 2 weeks ago


Singapur, Singapore TikTok Full time

About the team

The mission of the Data Business Partner (BP) Quality Assurance Team is to build a highly mature (standardized/professional/efficient) data quality system, ensuring the better delivery of data. Our goal is to safeguard the quality of data throughout the entire lifecycle in terms of timeliness, accuracy, and stability, empowering the enterprise's decision-making capabilities, market competitiveness, and operational efficiency. Team members possess rich backgrounds in big data technology and quality experience, along with keen data insight and a forward-looking technological perspective. We look forward to your contribution and joining our team What you will be doing:- Responsible for quality assurance work in offline/real-time data warehouses and data engineering, building a quality assurance system.- Develop comprehensive test plans and testing strategies based on actual business requirements, ensuring data accuracy and maintaining data engineering quality.- Quickly develop testing tools or platforms based on testing needs to improve business delivery efficiency.- Able to identify data system risks comprehensively, ensuring data system stability through means such as performance testing and online monitoring.- In-depth understanding of the business, communicate and collaborate with various roles in data business, create value for the business, and work without boundaries.- Update software, enhances existing software capabilities and develops and direct software testing and validation procedures.

- Bachelor's degree or above in computer science, mathematics, statistics, or related fields.- At least 2 years of experience in testing development/development work, with a preference for experience in big data testing and data engineering service testing.- Proficient in using one programming language (JAVA/Go/python) for tool development, skilled in using SQL, and preferably with independent experience in platform tool development.- Familiarity with common big data technologies such as Yarn, Spark, HDFS, understanding of data ETL processes, good literacy and foundation in mathematical analysis, and a solid background in statistics, data mining, and modeling are preferred.- Sensitivity to data, excellent logical thinking, analytical skills, business understanding, communication skills, and presentation abilities. - Strong initiative, sense of responsibility, and ability to work under pressure are required.
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