QA Engineer
Deeplight
| Company | Deeplight |
| Category | Engineering |
| Location | Dubai |
| Remote | On-site (inferred) |
| Employment | Contract |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 8 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (workable) |
Description
DeepLight AI is a specialist AI and data consultancy dedicated to transforming the regional corporate landscape through bespoke, high-impact intelligent systems. Based in the UAE, we partner with organizations across diverse sectors – with a deep-rooted expertise in Financial Services and Banking – to bridge the gap between complex data and actionable business strategy. At DeepLight, we don't believe in "off-the-shelf" fixes. We deliver tailored AI solutions designed to integrate seamlessly into existing enterprise architectures, ensuring that innovation is both scalable and secure. From building robust data foundations to deploying sophisticated AI platforms, we empower our clients to lead in an increasingly automated world. On a data platform, the thing under test is the data. As a QA Engineer, you own how we prove our platforms work end to end – from the pipelines that move and transform data to the API layers that expose it. This is a verification role: you don't build the pipelines, you build the confidence that they are correct. You won't just be "checking boxes"; you will be thinking critically about how data flows from source to insight and out to the consumer, ensuring every transformation and every endpoint maintains the integrity required for high-stakes financial services environments. Your responsibilities as a QA Engineer include; Designing, building, and owning automated test suites – functional, integration, and end-to-end – embedded into CI so quality gates run continuously. Testing the platform's API layer through contract testing, schema validation, and end-to-end checks against externally-consumed and partner-facing data APIs. Performing rigorous source-to-target reconciliation and checksums to ensure no "silent failures" occur during complex AWS Glue or Data Factory transformations. Extending and running Soda Core checks across Bronze, Silver, and Gold layers, and verifying that quality gates fire correctly as part of your automated suites. Monitoring automated alerts, performing initial root-cause analysis on data drift or schema failures, and collaborating with squads to implement permanent countermeasures. Working alongside Data Engineering squads to embed automated validation into live data flows, and supporting the data contracts and OpenMetadata lineage that producers and consumers rely on. As an AI consultancy, our greatest asset is the expertise of our people. While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data engineering and actionable business value is what defines your success with Deeplight. We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills. You will be the face of our firm, tasked with building trust, articulating the "why" behind your technical decisions, and effectively "selling" your vision to high-level stakeholders. If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in. Requirements What we need from you: 2–4 years of experience in QA / test automation, ideally on data-intensive or backend platforms. Strong proficiency in SQL and Python for test automation, data validation, and scripting. Practical experience with API and contract testing (e.g. REST, schema/contract validation). Hands-on experience designing and maintaining automated test frameworks and CI-embedded suites. Practical understanding of Lakehouse architectures and the Medallion (Bronze/Silver/Gold) design pattern. Hands-on experience with AWS services (specifically S3, Glue, and Athena) or similar cloud data stacks. A degree in Computer Science, Data Science, Information Systems, or a related field. The ability to look beyond a failed check to understand the root cause and its broader business impact. An uncompromising eye for accuracy,
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