Data Infrastructure Engineer
- Design and implement resource-efficient, low-latency data pipelines.
- Explore, evaluate, and select suitable frameworks for data science and big data processing.
- Provide tools and best practices for data access control, data versioning, and migration strategies for other teams.
- Write clean, maintainable, and well-commented source code.
- Proactively address problems with a research-thinking mindset and critically think about the pros and cons of different approaches.
- Independently read relevant literature and share your insights and knowledge with other stakeholders.
- Work in a cross-functional team that takes ownership of the full software lifecycle.
- Collaborate with other teams to make optimal software architecture design decisions.
Requirements
- Master’s degree or PhD in computer science, electrical engineering, mechanical engineering, applied mathematics, or a related field.
- Expertise and exceptional track record in data engineering and operations, including SQL and noSQL databases, system security and access control.
- Familiarity with and knowledge of the advantages and disadvantages of data warehouses, data lakes, data pipelines and batch and stream processing.
- Exceptionally strong understanding of fundamentals and problem solving skills.
- Understanding of software development best practices, including coding standards, code reviews, design patterns, source control management, and test automation.
- Expertise in at least one programming language, including C, C++, Java, Python, JavaScript, or Go.
- Strong verbal and written communication skills.
- Consistently professional demeanor in alignment with our values of integrity and excellence in the workplace.
Benefits
- Work with experts from around the world
- Top-notch facility and compensation
- Fully English-speaking work environment in Taiwan
- Combination of the best aspects of a startup, academia, and a large international enterprise