Junior QA Engineer (Tracking & Analytics)

ROIcamp is a media buying team that works exclusively with the dating vertical. The parent company has been building and monetizing dating products since 2011; the team is 40+ people and fully remote. We buy traffic on Meta, Google, TikTok, push and native placements, and we measure ourselves on paying users rather than on leads.

About the role

Media buying rests on one quiet condition: the numbers have to be true. The Meta algorithm optimizes toward the events we send it, a buyer's bonus is calculated from the conversions the tracker recorded, and the decision to scale a campaign is made from a cohort in BI. When an event fires twice, arrives late, or loses its subid, all three mechanisms start running on false data, and it usually surfaces a week and several thousand dollars later.

This role exists so that week never happens. ROIcamp has worked in the dating vertical since 2011, and one lesson from that time is that tracking should be verified by someone other than the person who configured it. You report to the Tech Lead and work closely with the analyst and the buying team.

This is not an entry-level position. We have a separate Junior QA Engineer opening for that. Here we are looking for someone who has already tested web products or worked inside ad accounts and has at least once had to work out why a conversion never arrived.

What you'll do

• Verify the event map on landing pages: that every event fires exactly once, at the right moment, and carries a complete set of parameters.
• Test conversion delivery across all channels at once: the pixel in the browser, the Conversion API on the server, the postback into the tracker, and the event in GA4. A mismatch between them is our bug, not a platform quirk.
• Follow parameters end to end through click, landing, registration, subscription and payment, checking that the subid stays the same at every step. A subid is the identifier that ties a conversion back to a specific buyer and campaign.
• Catch duplicate firings and verify deduplication by event_id, since an event counted twice damages both the reporting and the algorithm's training.
• Reconcile numbers between the ad account, the tracker and the BI dashboard, locate the source of the discrepancy, and describe it so an engineer can reproduce it after a single read.
• Test landings and prelanders before traffic goes live: layout, loading speed and forms across devices, browsers and GEOs. A prelander is the short intermediate page between the ad and the main offer page.
• Check redirects, rotation rules and the correctness of deeplink transitions into the app.
• Catch regressions after updates. Every bug that gets through becomes a new line in the test matrix, which is yours to maintain and extend.

Requirements

• Around a year of web testing experience, or an adjacent role where you regularly investigated why data did not add up.
• Hands-on exposure to advertising: you have seen an ad account from the inside and understand where a conversion in a report comes from.
• Confident use of DevTools: the Network tab, reading requests, parameters, cookies and redirect chains.
• A grasp of basic web mechanics: GET and POST, query parameters, response codes, and the difference between a client-side and a server-side event.
• Willingness to read JSON without hesitation and to write findings up in a structured way rather than as "something is broken".
• Consistency: the test matrix gets completed even when everything appears to be fine.

Nice to have

• Google Tag Manager and GA4, either configured yourself or at least understood well enough to read someone else's container.
• Experience with a tracker such as Keitaro, Binom or any equivalent.
• Postman or a similar tool for checking postbacks by hand.
• Basic SQL, enough to pull a number from a table yourself instead of asking the analyst.
• An understanding of mobile attribution and mobile measurement partners such as AppsFlyer.
• English sufficient for reading platform documentation.

What we offer

• Work on the live tracking behind dating traffic rather than a training environment: real volumes, real GEOs, real event counts.
• Rare expertise at the intersection of QA, advertising and analytics. There are few such specialists on the market, and they gain value faster than general testers.
• A visible result: you can see how much budget a broken event you found protected.
• Direct access to the Tech Lead and the analyst, so questions get settled in one message rather than three approvals.
• Fully remote work, full salary from day one, and payouts on a fixed date.

Growth path

The shortest path from here leads to the tracking infrastructure engineer: first you verify someone else's event map, then you design your own. The second direction is marketing analytics, since you already work with the same cohorts as the BI analyst, only from the other side. We discuss both moves at the six-month review and measure them by results rather than by tenure.

Compensation

$300 to $500 base, depending on how independently you can handle tracking from the start. Salary review after six months. Payouts on a fixed date each month.

Hiring process

A 30-minute screening call, then a practical task on a test landing page with broken tracking (up to two hours, reviewed together), then an interview with the Tech Lead, then an offer. The whole process takes up to 8 business days from your application.