Senior Data Engineer

KKCompany Technologies, Asia’s leading AI multimedia technology group is dedicated to creating values for customers with core businesses of multimedia technologies, digital cloud, and AI applications.

At KKCompany, we believe “Innovation Made Simple,” and technology is the answer to the struggles faced by every industry. Since its establishment two decades ago, KKCompany has expanded its portfolio, including KKBOX, BlendVision and Going Cloud. KKBOX is the world’s first platform bringing legal music streaming service to the public. It utilizes state-of-the-art streaming technology to enable excellent user experience. Our flagship brands and a base of international clients enable us to accumulate extensive data and advance analytical capabilities. The strengths along with our abundant experience in brand management help businesses achieve digital transformation successfully. We serve over tens of millions of consumers and enterprise clients in Asia cross a broad spectrum of industries such as telecommunication, multimedia, online education, fitness, smart retail and more.

KKCompany now has over 500 employees across offices in Tokyo, Singapore, Taipei, Kaohsiung, and Hong Kong.

What is a Data Engineer?

Data engineers are mainly tasked with transforming data into a format that can be easily productized. They do this by developing, maintaining, and testing infrastructures for data generation. Data engineers work closely with data scientists and are largely in charge of architecting solutions for data scientists that enable them to do their jobs.

Responsibilities:

• Take ownership and increase automation of the complex data flow to enable rapid experimentation in a nimble engineering organization.
• Support to implement the business logic to be compatible with real-time/stream processing frameworks.
• Implement anomaly detection techniques for data quality to surface metric shifts on datasets with dozens of dimensions.
• Improve internal process improvements including automating manual processes, optimizing data delivery, and re-designing infrastructure for scalability.

Requirements:

• Distributed data processing at scale (Spark, Hadoop or AWS)
• Large-scale storage and retrieval (Hadoop, ElasticSearch or Druid)

Nice To Have:

• Experience with Infrastructure-as-code (IaC) tools (AWS CloudFormation or Terraform).
• Programming experience manipulating and analyzing data (Scala, Java or Python, Golang)
• Autonomy in managing cross-functional engineering projects