Data Infrastructure Engineer

Roles & responsibilities

• 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.

Qualifications

• 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.