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QA Engineer – Scientific Software / Life Sciences / IoT Systems (Information Technology)/ 2 days ago

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Job Preference:

Preferred Exposure & Domain Relevance

Life Sciences / Pharma / Biotech

Useful for understanding regulated workflows and validation discipline.

Laboratory Software

Exposure to LIMS, ELN, CDS, scientific data systems, or lab workflow software is preferred.

Analytical Instruments

Experience with instrument-connected applications or scientific equipment software is an advantage.

IoT / Device Software

Useful for testing device status, connectivity, telemetry, logs, and data acquisition workflows.

Healthcare / MedTech

Helpful for quality, traceability, and compliance-oriented testing.

Industrial Automation

Useful for understanding device-driven workflows, alerts, and operational reliability

Qualification:

Job Description:

We are looking for a detail-oriented QA Engineer with experience or strong interest in scientific software, life sciences, laboratory systems, healthcare, device-connected platforms, or regulated software environments.

The selected candidate will be responsible for testing complex software applications involving laboratory workflows, instrument-connected systems, data processing, calculations, reporting, audit trails, and validation-oriented quality processes.

This role requires strong functional QA skills, analytical thinking, documentation discipline, and the ability to work closely with developers, business analysts, technical leads, domain experts, and client stakeholders.

Key Responsibilities

Functional Testing

Perform manual, regression, integration, system, and end-to-end testing of scientific and instrument-connected software applications.

Workflow Validation

Understand and validate workflows such as method setup, sequence creation, data processing, result review, reporting, and audit trail.

Test Case Preparation

Prepare detailed test scenarios, test cases, test data, and execution reports based on requirements and acceptance criteria.

Data & Result Validation

Validate calculated outputs, result tables, units, flags, pass/fail status, rounding rules, and summary values.

Report Testing

Verify generated reports against expected/reference outputs and ensure data correctness, traceability, and consistency.

Audit Trail Testing

Validate audit logging for key user actions, changes, recalculations, approvals, report generation, and data updates.

Defect Management

Log clear defects with reproducible steps, screenshots/logs, expected vs actual behavior, severity, and business impact.

UAT Support

Support UAT planning, execution, defect triage, evidence collection, and acceptance sign-off.

Regression Testing

Ensure new features do not impact existing workflows, calculations, reports, or data integrity.

Automation Support

Identify repeatable test scenarios and support automation teams in building regression suites.

Documentation

Maintain test plans, test cases, execution summaries, defect reports, traceability matrices, and QA evidence packs.

Skills:

Required Skills & Skills Requirement

Manual QA

Strong hands-on experience in functional, regression, integration, and end-to-end testing.

Test Design

Ability to convert requirements, workflows, and acceptance criteria into structured test cases.

API Testing

Working knowledge of REST APIs, Postman, JSON, request/response validation.

Database Testing

Ability to execute basic SQL queries and validate backend data.

Defect Reporting

Strong ability to document defects clearly and work with development teams for resolution.

Documentation

Experience preparing test plans, test cases, test reports, and QA evidence artifacts.

Analytical Thinking

Ability to identify edge cases, data mismatches, calculation issues, and workflow gaps.

Communication

Good written and verbal communication skills for working with technical and domain teams.

Good-to-Have Skills & Skill Description

Test Automation

Selenium, Playwright, Cypress, API automation, or equivalent tools.

Python Scripting

Useful for data comparison, file validation, report comparison, and automation utilities.

Report Comparison

Experience comparing PDF, Excel, CSV, or generated reports against expected outputs.

Scientific Data Testing

Ability to validate numeric values, units, rounding, calculations, and result consistency.

Compliance Exposure

Familiarity with audit trail, electronic records, validation documentation, or 21 CFR Part 11 concepts.

CI/CD Exposure

Understanding test execution in pipelines and regression dashboards.

Qualification Criteria & Requirement

Education

B.E./B.Tech/MCA/M.Sc./B.Sc. in Computer Science, Life Sciences, Biotechnology, Instrumentation, Electronics, or related field.

Experience

3–6 years of QA experience in software testing.

Domain Preference

Life sciences, healthcare, laboratory software, IoT, analytical instruments, or regulated software experience preferred.

Technical Skills

Manual testing, API testing, SQL basics, defect management, documentation.

Mindset

Detail-oriented, analytical, process-driven, quality-focused, and willing to learn scientific workflows.

Collaboration

Work effectively with developers, BAs, technical leads, and domain SMEs.

Quality Ownership

Think beyond UI testing and validate end-to-end workflow correctness.

Domain Adaptability

Quickly learn scientific and instrument-connected software concepts.