Senior Bioinformatics Engineer

At Twist Bioscience, a Senior Bioinformatics Engineer designs and implements production-grade bioinformatics pipelines for processing NGS data. This role involves architecting cloud-native infrastructures, optimizing workflows, and collaborating with scientific teams to improve biological research.

To qualify for the Senior Bioinformatics Engineer role at Twist Bioscience, candidates should have at least five years of software engineering experience, advanced programming skills in languages like Python, Rust, or C#, and strong knowledge of CI/CD tools and cloud services.

Applying for the Senior Bioinformatics Engineer position at Twist Bioscience offers a fantastic opportunity to work with cutting-edge sequencing technologies and to contribute to projects that have a tangible impact on health and technology across various fields.

Key responsibilities of the Senior Bioinformatics Engineer at Twist Bioscience include designing bioinformatics pipelines, maintaining cloud infrastructure, collaborating with research teams, and ensuring that the systems are scalable and reliable.

Candidates for the Senior Bioinformatics Engineer role at Twist Bioscience should be proficient in programming languages such as Python, Rust, or C#, as well as familiar with Linux scripting and container orchestration.

A Senior Bioinformatics Engineer at Twist Bioscience works with technologies such as AWS cloud services, CI/CD tools like Docker and Jenkins, and container orchestration platforms like Kubernetes to build and maintain bioinformatics pipelines.

Twist Bioscience offers a collaborative and innovative work environment for Senior Bioinformatics Engineers, where they work alongside scientists and engineers to push the boundaries of technology in the bioinformatics space.

In your response, highlight specific pipelines you've designed or worked on, discuss the technologies you used, and emphasize the impact these systems had on research or analysis.

Discuss your hands-on experience with cloud services like AWS, detailing how you've leveraged these environments in bioinformatics contexts—mention specific examples of projects where you utilized these technologies.

Explain the strategies you implement to maintain scalability, reproducibility, and reliability, such as monitoring, testing practices, and CI/CD pipelines.

Provide a specific instance where you faced a technical challenge, outlining the problem-solving steps you took and the solutions you implemented with measurable results.

Share your approach to effective communication and teamwork, providing examples of past collaborations and the outcomes that were achieved through these efforts.

Discuss your proficiency in programming languages relevant to the role, such as Python or Rust, and share examples of how these languages have enabled you to solve bioinformatics challenges.

Elaborate on your practical experience with Docker and Kubernetes, illustrating particular projects where you used these tools to enhance the deployment and scalability of bioinformatics workflows.

Talk about your experience implementing CI/CD methodologies, including tools you've used, and how these practices have benefited your prior projects in building and maintaining bioinformatics tools.

Explain your approach to version control, emphasizing tools like Git, and how you utilize version control principles to manage code integrity in bioinformatics development.

Discuss your methods for continual learning in the bioinformatics field, whether through journals, conferences, online courses, or participation in professional organizations.