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Manager Biotech Software Engineer Jobs in Texas (NOW HIRING)

Danaher

About Software Engineering Roles at Danaher Are you passionate about building real-world ... biotechnology. Our global teams work every day to solve the world's most complex challenges by ...

Danaher

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Danaher

Software Engineer Internships

Beaumont, TX · On-site

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Danaher

About Software Engineering Roles at Danaher Are you passionate about building real-world ... biotechnology. Our global teams work every day to solve the world's most complex challenges by ...

Danaher

Software Engineer Internships

San Marcos, TX · On-site

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Danaher

Software Engineer Internships

Arlington, TX · On-site

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Danaher

Software Engineer Internships

El Paso, TX

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Software Engineer Internships

Mckinney, TX · On-site

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Danaher

Software Engineer Internships

Dallas, TX

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Danaher

Software Engineer Internships

Austin, TX · On-site

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Danaher

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All JobsBiotech Software Engineer JobsManager Biotech Software Engineer JobsManager Biotech Software Engineer Jobs in Texas

Manager Biotech Software Engineer information

What is the difference between Manager Biotech Software Engineer vs Biotech Software Engineer?

AspectManager Biotech Software EngineerBiotech Software Engineer
Required CredentialsBachelor's or Master's in Biotechnology, Software Engineering, or related field; experience in biotech software development; leadership skillsBachelor's or Master's in Biotechnology, Computer Science, or related field; programming skills; biotech industry knowledge
Work EnvironmentLeads teams, manages projects, collaborates with cross-functional teams in biotech companiesDevelops biotech software solutions, collaborates with scientists and engineers, works in R&D labs or software teams
Employer & Industry UsageUsed by biotech firms, pharmaceutical companies, research institutionsCommon in biotech R&D, pharmaceutical software development, biotech startups

The main difference is that a Manager Biotech Software Engineer oversees teams and manages projects, while a Biotech Software Engineer focuses on developing software solutions. The manager role involves leadership and strategic planning, whereas the software engineer role emphasizes technical development and coding.

What are the most commonly searched types of Biotech Software Engineer jobs in Texas?

The most popular types of Biotech Software Engineer jobs in Texas are:

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For Manager Biotech Software Engineer jobs in Texas, the most frequently searched job titles are:

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The top searched job categories for Manager Biotech Software Engineer jobs in Texas are:

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Cities in Texas with the most Manager Biotech Software Engineer job openings:

Manager Biotech Software Engineer jobs near you

Automation QA Engineer - Genomics / Bioinformatics - San Diego CA - Onsite Day One

Vytwo

Dallas, TX • On-site

$105 - $145/hr

Other

Medical, Life

Posted 7 days ago

Job description

Title: Automation QA Engineer – Genomics / Bioinformatics

Domain: Bioinformatics

Location: San Diego, CA - Onsite Day One

Duration: 6 Months

Job Description: We are hiring an Automation QA Engineer to test software systems used in genomics and life sciences workflows. This is a quality engineering role, not a bioinformatics pipeline development role: you will design, build, and execute automated and manual test coverage for platforms that process genomic and laboratory data, and you will validate that results align with real wet lab and dry lab processes. Strong Python-based test automation skills are essential; genomics/BioE domain knowledge is what separates a good tester on this platform from a great one.

Key Responsibilities
  • Design, develop, and maintain automated test suites (Python-based) for applications supporting genomics, sequencing, and life sciences data workflows.
  • Build and execute test plans, test cases, and regression suites covering functional, integration, and data‑validation testing — no pipeline‑building responsibility; the focus is verifying pipeline/application outputs, not authoring bioinformatics pipelines.
  • Validate software behavior against genomic science concepts (e.g., sequencing data types, variant calling outputs, sample-to-result traceability) to confirm results are scientifically and technically correct.
  • Coordinate directly with wet lab and dry lab teams to understand sample lifecycle, instrument outputs, and data handoffs, and translate that understanding into test scenarios.
  • Test integrations with LIMS (Laboratory Information Management Systems), ensuring sample tracking, chain‑of‑custody, and result reporting behave correctly end‑to‑end.
  • Identify, document, and track defects; partner with engineering and product teams on root‑cause analysis and resolution.
  • Contribute to test strategy for healthcare/life sciences compliance considerations (e.g., data integrity, audit trail, traceability) in partnership with QA leadership.
  • Continuously improve automation frameworks, CI/CD test integration, and test data management practices.
Required Qualifications

Education: Bachelor's or Master's degree in Computer Science, Bioinformatics, Bioengineering, or a closely related field.

Experience & Technical Skills
  • 3+ years of experience in QA / test automation, with hands‑on Python scripting for test frameworks (e.g., pytest, unittest, Robot Framework).
  • Working knowledge of genomics science fundamentals — sequencing concepts, sample-to‑data lifecycle, common file/data formats used in genomics.
  • Demonstrated experience in Life Sciences or Biotech software environments (not general enterprise QA alone).
  • Direct exposure to wet lab and/or dry lab environments, with the ability to coordinate testing activities against real lab processes and instrument/data outputs.
  • Experience testing or interacting with LIMS platforms.
  • Comfortable working without owning pipeline construction — this role validates genomics data/software outputs; it does not develop bioinformatics pipelines.
Preferred / Bonus Qualifications
  • Prior experience specifically as an Automation QE within a Bioinformatics organization.
  • Familiarity with cloud‑based genomics platforms or data lakes used in life sciences software.
  • Exposure to regulatory/compliance frameworks relevant to healthcare and life sciences software (e.g., HIPAA, CLIA, CAP, 21 CFR Part 11) — awareness level, not ownership.
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