The Data Engineering Group is a growing diverse team and responsible for building the company's biggest data pipeline - collecting and processing billions of events daily.
They are looking for experienced data engineers and data wranglers who enjoy optimizing data and building them from the ground up.
‐ Build and maintain large-scale batch and real-time data pipelines with data processing frameworks and technologies like Spark, Flink, Kafka, Druid etc.
‐ Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
‐ Improve data quality through testing, tooling and continuously evaluating performance.
‐ Work in cross functional agile teams to continuously experiment, iterate and deliver on new product objectives.
‐ Work with data and analytics experts to strive for greater functionality in our data systems.
Our client is a large global Internet service company that has enjoyed sustained growth as they continue to expand their business in various new areas and industries. This is a great opportunity to work in a diverse and international environment in Japan. Our client actively strives to be an equal opportunity employer, and they have many female and foreign nationals in upper management positions. Their brand has also gained global recognition as they sponsor some of the world's most famous sports teams. Our client prides themselves in providing a comfortable working environment for their employees. Engineers are welcome to choose their own setup (Windows/Mac, etc.); whatever makes them comfortable! Free meals are also provided at the company cafeteria. Their chefs work to create exciting new menus and dishes, so employees never get tired of the food!
9:00 - 17:30（Mon - Fri）
Saturday, Sunday, and National Holidays, Year-end and New Year Holidays, Paid Holidays, Other Special Holidays
【Services / Benefits】
Social insurance, Transportation Fee, Skillhouse Benefit, No smoking indoors allowed (Designated smoking area), etc.
‐ Experience in data engineering experience with streaming technologies.
‐ Know how to work with high volume heterogeneous data tools such as Spark, etc.
‐ Experience performing root cause analysis on data and processes to find anormal trend in the log and improved data quality through testing.
‐ Knowledgeable about data analytics frameworks and experience of Business Intelligence and jupyter, such like analytics tool.
‐ Care about agile software processes, data-driven development, reliability, and responsible experimentation.