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HG - 644

QA Engineer (Remote)

India · 3-8 years · Permanent

Location
India
Experience
3-8 years
Job type
Permanent
Reference
HG - 644
Domain
Information Technology and Services

QA Engineer,  AI Integration – AI Technology Company – Remote (Dubai)

About the role:  A leading Dubai based AI Integration and AI Tech startup  is looking for a QA Engineer who is passionate about data quality, analytical thinking, and building robust test coverage for a data-heavy SaaS product.

This is not a click-through manual testing role. You will be embedded in our engineering process, owning quality across three domains:

  1. Product & Frontend QA — test the dashboard UI and user flows end-to-end
  2. API & Integration Testing — validate the correctness and reliability of our backend REST APIs
  3. Data Pipeline QA — verify the accuracy of scraped data, DB migrations, data promotions, and the metrics/KPIs surfaced on the dashboard

The third area is where they need the sharpest skills. Their platform collects data via scrapers, transforms and promotes it through staging tables into production, and then aggregates it into reports and dashboards. Every number on the screen must be traceable to the source data — and you will be the person who ensures that chain of truth holds.

As they grow and onboard more customers with more data, performance testing will become an increasing part of the role. They want someone who can grow into that responsibility.

About the Company: Our client is engaged in the business of building core AI-powered data orchestration and automation platform designed to operate on top of existing enterprise systems. They develop reusable core technology for healthcare, professional services, manufacturing, and other regulated industries, supported by experienced financial and strategic partners for long-term focus and disciplined execution.

Location: Remote

Designation: QA Engineer

Reports to: Head of Engineering / CTO

Roles and Responsibilities:

Data Pipeline & Migration QA

  • Validate data collected by scrapers against source portal data — catch missing records, field mapping errors, and encoding issues before they reach production
  • Write SQL queries to verify data integrity across staging (iws_*) and production tables after promotions and migrations
  • Assert row counts, field values, nullability, uniqueness constraints, and referential integrity after each data movement
  • Detect and document regressions when scraper behaviour changes or new portal connectors are added
  • Build reusable SQL-based validation scripts that can be run after every data promotion cycle

API Testing

  • Test REST API endpoints for correctness: response schemas, HTTP status codes, filter logic, pagination, edge cases
  • Validate that API responses correctly reflect the underlying database state — especially aggregated KPIs, trend data, and filtered results
  • Write and maintain automated API test suites (Postman collections, pytest, or equivalent)
  • Test authentication flows, role-based access control, and error handling

Product & Frontend QA

  • Test dashboard features end-to-end: claims views, reimbursements, filters, account switching, billing flows
  • Identify UI regressions across browsers and screen sizes
  • Validate that frontend data displays (tables, charts, KPIs) match what the API returns and what is in the database
  • Write clear, reproducible bug reports with steps, expected vs actual, and supporting SQL evidence where relevant

Quality Process

  • Participate in sprint planning and design reviews — flag testability concerns early
  • Maintain a living test plan covering critical paths, edge cases, and known fragile areas
  • Own the QA sign-off process before any data promotion from staging to production
  • Contribute to test automation infrastructure over time

Requirements:

Must-Have Skills

  • Strong SQL — you must be comfortable writing complex queries: joins across multiple tables, aggregations, window functions, subqueries, CTEs. SQL is your primary tool for verifying data correctness.
  • Healthcare or medical industry experience — you understand the domain, the data sensitivity, and the importance of accuracy in a clinical/insurance context
  • API testing experience — hands-on with REST API validation (Postman, HTTPie, or similar); understanding of request/response cycles, auth headers, and HTTP semantics
  • Analytical and critical thinking — you don't just test what you're told to test. You ask "what could go wrong with this data" and go find it.
  • Strong communication — you write clear bug reports, ask sharp questions in technical discussions, and can explain a data discrepancy to a non-technical stakeholder
  • Attention to detail — in a data product, a 1-row discrepancy in a 10,000-row table matters. You notice it.

Nice-to-Have Skills

  • Python — scripting for test automation, data validation scripts, or scraper QA. Not mandatory, but a significant plus given how data-heavy our stack is.
  • Performance testing — experience with tools like k6, Locust, or JMeter. We will need this as our data volumes grow — early experience here is valued.
  • Understanding of web scraping — familiarity with how scrapers work (HTML parsing, session management, pagination) will help you QA our collectors more effectively
  • ETL / data pipeline experience — having worked on or tested data transformation and promotion pipelines (even outside healthcare) is a strong plus
  • PostgreSQL — our database is Postgres. Knowledge of Postgres-specific features (JSONB, ON CONFLICT, EXPLAIN ANALYZE) is a bonus.
  • CI/CD awareness — understanding how test suites fit into a deployment pipeline (GitHub Actions, Cloud Build)
  • Familiarity with Django REST Framework or similar backend frameworks

Ideal candidate:

QA engineer who thinks like a data analyst. When see a number on a dashboard, first instinct is to trace it back to the database and verify it. Equally comfortable writing a SQL validation query and filing a detailed UI bug report. Have worked in healthcare or medical software and understand what it means when data is wrong in this domain. And are curious, systematic, and enjoy the detective work of finding exactly where the data went wrong.

Experience: 3+ years of QA experience in a software product environment

Working days: Monday-Friday

Perks and Benefits:

  • Competitive salary based on experience
  • Full-time remote-friendly role
  • Direct impact: you are not testing a toy — every QA decision you make affects real healthcare data for real customers
  • A small, fast-moving team where your work is visible and valued
  • Opportunity to grow the QA function from the ground up as the team and product scale
  • Paid time off and public holidays
  • Access to the latest tooling — you choose what helps you do your job besta

Interview process

  1. Screening call — 30 min, role overview and background check
  2. Technical interview 1 — SQL-based data validation task + API testing
  3. Technical interview — deep dive on your QA approach, a real scenario from our product
  4. Final conversation — meet the team, discuss fit and expectations

Contact Details: For more details on this vacancy, contact Ayush at ayush@hiregenie.in or +91 7892947566.

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Skills

  • CI/CD
  • ETL Testing
  • QA Engineering
  • restAPI
  • Python
  • PostgreSQL
  • SQL
  • Data Validation
  • Manual Testing
  • Quality Assurance Processes
  • Data Analysis
  • Good communication and written skill
  • Data Engineering
  • Data Analytics
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