Mirador is a next-generation precision medicine company focused on immunology and inflammation. The company’s Mirador360
TM precision development engine leverages the latest advances in human genetics and cutting-edge data science to rapidly advance new precision medicines for patients living with chronic immune-mediated inflammatory and fibrotic diseases. Launched in 2024, Mirador has raised over $400 million from leading life sciences investors and is based in San Diego, CA.
Summary
We are seeking a highly skilled and experienced Senior Bioinformatics Platform Engineer with a strong focus on data and software engineering to join our innovative bioinformatics team. In this hybrid role, you will lead the design, development, and optimization of computational platforms and data pipelines on Amazon Web Services (AWS). You will be at the forefront of integrating bioinformatics data engineering with software development practices, ensuring our platforms and tools are robust, scalable, and efficient for large-scale genomic and biological data analysis.
Responsibilities
Data Engineering Leadership: Lead the design and implementation of robust data pipelines for processing, storing, and analyzing large-scale genomic and biological datasets. Develop ETL processes to ensure efficient data flow and integration across platforms.
Software Development: Contribute to and lead the development of bioinformatics software tools and applications, ensuring they are well-integrated with data pipelines and platforms. Work closely with software engineering teams to apply best practices in software development, including version control, code review, testing, and documentation.
Cloud Infrastructure Management: Architect, build, and manage AWS cloud infrastructure using Infrastructure as Code (IaC) tools like Terraform or CloudFormation. Optimize AWS services (e.g., EC2, S3, Lambda, RDS, ECS/EKS) specifically for data-intensive bioinformatics workflows.
Performance Optimization: Monitor and enhance platform and pipeline performance, focusing on scalability, efficiency, and cost-effectiveness. Develop strategies for high availability, data redundancy, and disaster recovery.
Automation and CI/CD Pipelines: Develop and maintain automation scripts and CI/CD pipelines to streamline the deployment of software applications and data pipelines. Ensure that updates and new releases are managed efficiently and with minimal disruption to operations.
Data Security and Compliance: Implement and enforce data security best practices and ensure all platforms and pipelines comply with relevant regulations (e.g., HIPAA, GDPR) for handling sensitive genomic and clinical data.
Collaboration and Mentorship: Collaborate with bioinformaticians, data scientists, and other engineers to understand computational and data requirements. Mentor junior engineers and foster a culture of continuous learning and improvement within the team.
Documentation and Training: Maintain comprehensive documentation of platform architecture, data pipelines, and software development processes. Provide training and support to team members and stakeholders on platform and pipeline usage.
Experience and Qualifications
Bachelor’s or Master’s degree in Bioinformatics, Computer Science, Computational Biology, Data Engineering, or a related field.
5 years or more of experience in bioinformatics or computational biology, with a focus on cloud-based platforms and data engineering.
5 years or more of experience in managing and optimizing AWS infrastructure, with a strong track record of using services like EC2, S3, Lambda, RDS, ECS/EKS, and VPC.
Proven experience with Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or AWS CDK.
Extensive experience in software development, including proficiency in Python, Java, or similar programming languages.
Strong background in data engineering, including designing ETL pipelines and working with large-scale biological datasets.
Certifications: AWS Certified Solutions Architect (Professional) or AWS Certified DevOps Engineer (Preferred).
Skills and Abilities
Deep understanding of bioinformatics tools, workflows, and data formats (e.g., FASTQ, BAM, VCF).
Expertise in data engineering tools and technologies, such as Apache Spark, Hadoop, and data lakes.
Proficiency in programming languages such as Python and R for data analysis and pipeline development.
Strong experience in Linux/Unix systems administration and shell scripting.
Experience with containerization and orchestration tools such as Docker and Kubernetes.
Strong experience with CI/CD tools and practices, such as Jenkins, GitLab CI, or AWS CodePipeline.
Familiarity with database management systems (SQL and NoSQL) and data warehousing solutions.
Knowledge of data security and compliance standards (HIPAA, GDPR) related to genomic data.
Strong analytical and problem-solving skills, with a proactive approach to identifying and solving technical challenges.
Excellent leadership and communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders.
The expected base pay range for this position is $125,000 – $195,000 plus bonus, equity, and comprehensive benefits. The base pay range reflects the target range for this position, but individual pay will be determined by additional factors such as job-related skills, experience and relevant education or training. This range may be modified in the future.
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