Data Infrastructure Engineer

Open 63d

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

What this application asks