Test Automation Engineering Manager (Biomedical Knowledge Base)

Quick Facts

• Role: Test Automation Engineering Manager (Biomedical Knowledge Base)

• Team: Lead 3–5 Test Automation Engineers and QA/QC specialists

Description

Lead, mentor, and develop a team responsible for validating the scientific quality, correctness, and scalability of biological content, analytics, and data pipelines. Stay hands-on by designing and executing scalable test methods to assess correctness and completeness of biological information and the accuracy and reliability of analytics and interpretations. Coordinate testing coverage and quality planning with cross-functional stakeholders and represent content QA during release planning and tracking.

Responsibilities

• Lead and mentor a team of 3–5 test automation and QA/QC engineers

• Define team priorities, testing strategies, and quality goals

• Partner with cross-functional stakeholders to coordinate testing coverage and manage content QA for release planning and tracking

• Review and refine data and software requirements, use cases, and workflows to ensure they are scientifically valid, technically robust, and testable

• Design and implement automated quality controls to improve reliability of processes, pipelines, tools, and models

• Own the test automation lifecycle for specific data, product features, or tools, including test approach design, implementation, and reporting

• Select or develop test automation tools and frameworks; contribute to continuous integration pipelines and infrastructure maintenance

• Document testing and validation efforts according to ISO 9001, ISO 13485, and IVDR

Requirements

• Undergraduate degree in bioinformatics, bioengineering, genetics, molecular biology, or a related field (graduate degree preferred)

• 5+ years of industry experience in bioinformatics, including test automation for production-grade tools and pipelines

• 2+ years of experience managing engineers or bioinformatics scientists

• Strong software development fundamentals with experience in multiple general-purpose languages including Python; comfort working in Linux

• Experience with git, code review, unit and integration testing, documentation, and collaborative development

• Human genetics/genomics domain knowledge and familiarity with tools/databases such as NCBI, Ensembl, RefSeq, ClinVar, COSMIC, and OMIM

• Practical experience with biomedical ontologies (Gene Ontology, Human Phenotype Ontology) and semantic technologies (RDF, OWL, SPARQL)

• Data modeling experience using SQL and non-relational/graph databases such as Neo4j

• Experience with information extraction and knowledge modeling for structured and unstructured biological data (preferred)

• API testing and browser-based automation tools (Selenium, WebDriver) (plus)

Benefits

• Bonus/commission, local benefits

• Referral program and volunteer day

• Internal academy (QIALearn) and employee assistance program

• Hybrid work (conditional to role)

• Estimated base salary range: $130,000–$154,000; total compensation includes a bonus plan and generous benefits