Senior Software Engineer, Data Backend (Ad Cloud)
About this role
Writing clean Python code for RESTful APIs, building scalable data warehouses, and orchestrating pipelines with Apache Airflow and Apache Spark make up the daily routine of this engineering position. The data backend team at Appier focuses on developing critical infrastructure that supports proprietary deep learning and machine learning solutions, allowing businesses to transform raw data into actionable insights. Engineers in this group collaborate with cross-functional teams to automate operational workflows, maintain robust monitoring systems, and deploy containerized services on cloud platforms.
Appier created this role to strengthen its Agentic AI as a Service platform and expand its global ad cloud capabilities from Taipei. A successful candidate brings a strong foundation in distributed systems, big data architectures, and modern AI-assisted development tools. Independent problem solvers who thrive in fast-paced environments and adapt quickly to shifting project priorities will find themselves right at home within this engineering culture.
What you will do
- Design, develop, and maintain RESTful APIs using Python.
- Build and manage robust data warehouses utilizing ClickHouse, Trino/Presto, and Pinot.
- Design and develop data pipelines using Apache Airflow and Apache Spark.
- Work closely with cross-functional teams to develop automation tools that streamline daily operations.
- Implement state-of-the-art monitoring and alerting systems to ensure optimal system performance and stability.
- Address queries from applications in a timely and effective manner, ensuring high client satisfaction.
- Work on cloud platforms such as AWS and GCP, leveraging their capabilities to optimize data operations.
- Utilize Kubernetes for container orchestration to facilitate efficient deployment and scaling of applications.
What you need
- Hold a BS or MS degree in Computer Science.
- Bring at least two years of experience in building and operating large-scale distributed systems or applications.
- Demonstrate hands-on experience in Kubernetes development and Linux or Unix environments.
- Show proven experience in managing data lakes or data warehouses.
- Possess expertise in developing data structures and algorithms on top of Big Data platforms.
- Demonstrate high proficiency in AI-assisted development workflows using tools such as Cursor, Claude Code, or Gemini.
- Exhibit a solid understanding of agentic coding paradigms and multi-step, tool-augmented AI development pipelines.
- Operate effectively and independently in a dynamic, fluid, and fast-moving team environment.
Nice to have
- Experience working with DuckDB, Druid, and ClickHouse
- Contributions to open source projects with a provided GitHub link
- Experience working with Python, Scala, or Java
- Experience with Hadoop, Hive, Flink, Presto, and Trino
- Experience with Public Cloud platforms like AWS or GCP
Skills and tech stack
Questions candidates ask
What tools and frameworks will I use on the data backend team?
You will design RESTful APIs using Python, build data warehouses with ClickHouse, Trino/Presto, and Pinot, and manage data pipelines using Apache Airflow and Apache Spark. The team also relies on Kubernetes for container orchestration and AWS or GCP for cloud operations.
What qualifications are required for this position?
Candidates must have a BS or MS degree in Computer Science along with at least two years of experience building and operating large-scale distributed systems. Additional requirements include experience with Kubernetes, Linux/Unix, data lake or data warehouse management, and proficiency in AI-assisted development workflows.
What kind of work environment should I expect?
You will work in a fast-moving team environment that requires juggling many tasks and projects while operating effectively and independently in a dynamic, fluid setting.