QA Engineer (Manual + Automation)

QA Engineer (Backend / Data Systems)
📍 Surat, Gujarat, India | Full-time, Onsite | 3–5+ Years Experience
Who We Are
Alphabin is a QA consulting firm — testing is what we do, not a box we check before shipping. We work with startups and established companies alike, and our job is simple: make sure the software actually works the way it's supposed to, before the customer finds out otherwise.
The Role
We're looking for a QA engineer who's comfortable going deeper than "does the button work." This role is about data — following it from the moment it enters the system, through processing, all the way to the report or dashboard someone's looking at, and making sure it's correct at every step, not just present.
Think: data flowing in from external sources, moving through Kafka, landing in MongoDB or Postgres, getting crunched into numbers that actually matter to a business — and you're the person who catches it when something quietly goes wrong along the way.
You won't just be trusting what the API tells you. You'll be querying the database yourself to check.
What You'll Actually Be Doing
Testing the whole pipeline, start to finish — not just one layer of it.
Digging into whether the numbers are actually right — the calculations, the edge cases, what happens when a device or data source goes offline, what happens during a backfill.
Checking new integrations before they go live — making sure field mappings are right, sign conventions are right, and things don't break on weird partial or malformed data.
Making sure that when something fails in the pipeline, it fails loudly — not silently dropped somewhere with no trace.
Running API regression tests (Postman, automated suites) and keeping those collections in good shape.
Writing SQL queries to independently verify that what the pipeline produced actually matches the raw source data.
Building regression suites that catch breaking changes before they hit production — across a codebase that spans a few different languages and repos.
When something looks off in production, tracing it back to the exact service or job responsible, and writing it up clearly enough that an engineer can act on it immediately — not "this seems broken."
Building and growing automated test suites (UI and API) using tools like Playwright, Selenium, REST Assured, or Appium.
Plugging your automated tests into CI/CD so problems get caught before release, not after.
Using AI tools day-to-day to write and maintain test scripts faster — we're not precious about doing things the slow way if there's a better way.
Working closely with developers and product folks to clear up ambiguity early, instead of discovering it during testing.
What We'd Like You to Bring
3–5 years of QA experience, with real time spent testing backend or data systems — not just UI testing.
You're comfortable writing your own SQL to check things yourself, rather than taking data at face value.
Solid API testing chops — Postman, REST concepts, auth tokens, reading Swagger/OpenAPI docs.
An understanding that in async systems, "the fix went out" and "the data is fixed" aren't the same moment — you know how to test around that gap.
Bug reports that give people what they need: a hypothesis, exact steps, and the actual scope of what's affected.
Enough scripting ability (Python or Node) to knock together a quick script to check something yourself.
Experience setting up automation frameworks from the ground up, not just adding to an existing one.
Clear written and verbal communication — you can explain a bug so someone else doesn't have to guess what you meant.
Nice-to-Haves (Not Dealbreakers)
You've tested IoT or telemetry data before — device streams, offline/reconnect behavior, timestamp headaches across time zones.
You've worked with Kafka or similar event-streaming systems.
You know your way around ClickHouse or another time-series database.
You've tested a platform that serves both consumer and business customers.
You can read Java or Go well enough to follow the logic, even if you're not writing it.
You've worked in energy, solar, utilities, or another technical domain.
You've worked in Agile/Scrum teams and used tools like Jira or TestRail.
What Success Looks Like After 90 Days
You can trace a reported bug from the dashboard all the way back to the raw data yourself, without needing an engineer to hold your hand.
You've built a reusable checklist for onboarding new integrations that the team actually keeps using.
You've made AI tools (ChatGPT, Claude, Copilot, testRigor, whatever works) a real part of how you write tests and dig into bugs faster.
You've caught at least one real calculation bug by querying data directly — before it ever reached a customer.
Why This Role Is Different
Here, QA isn't the last checkbox before a release — it's treated as core to how we build things. You'll get exposure to real, data-heavy systems and a variety of tech stacks, which tends to mean faster growth than testing the same single product for years.
Why Alphabin
Fair, competitive pay
Projects that actually matter to the clients we work with
A team that treats QA like a craft, not an afterthought
Constant exposure to new tools, tech, and problems worth solving
Room to keep learning and grow your career
Sound like your kind of problem to solve? We'd love to hear from you. 🚀

Work arrangement
No