7 months ago
Tokyo, JapanStaff+
Responsibilities
- Design, develop, and maintain APIs using Python.
- Build and manage data warehouses using Trino/Presto and Pinot.
- Design and develop data pipelines using Apache Airflow and Apache Spark.
- Develop automation tools with cross-functional teams to streamline daily operations.
- Implement monitoring and alerting systems for system performance and stability.
- Address application queries promptly and effectively.
- Use AWS and GCP to optimize data operations.
- Use Kubernetes for container orchestration, deployment, and application scaling.
Requirements
- BS or MS degree in Computer Science.
- 3+ years of experience building and operating large-scale distributed systems or applications.
- Experience with Kubernetes development and Linux/Unix.
- Experience managing a data lake or data warehouse.
- Expertise developing data structures and algorithms on Big Data platforms.
- Experience with Python, Scala, or Java is preferred.
- Experience with Hadoop, Hive, Flink, Presto/Trino, and related big data systems is preferred.
- Experience with public cloud platforms such as AWS or GCP is preferred.
- Open-source project contributions are a plus.
Tech Stack
Apache AirflowApache FlinkApache HadoopApache HiveApache SparkAWSGoogle Cloud PlatformJavaKubernetesLinuxPrestoPythonScala
About Appier
Appier is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value with cutting-edge AdTech and MarTech solutions. Guided by the vision of “Making AI Easy by Making Software Intelligent,” our mission is to help businesses turn Agentic AI into ROI. Founded in 2012, Appier is listed on the Tokyo Stock Exchange’s Prime Market (Ticker: 4180) and operates in 17 cities worldwide, enabling over 2,000 leading companies to enhance marketing performance with the latest AI technology. As AI enablers for our customers in the AI Era, Appier delivers innovative solutions that drive measurable results.