Job at a Glance
- π Location: Dubai, United Arab Emirates
- π’ Company: Nameless Ventures
- πΌ Employment Type: Full-time
- π Seniority: Mid-Senior level
- ποΈ Function: Engineering
- π Industry: Staffing and Recruiting
- π Date Posted: 2026-08-14
- π Category: Software Engineering
About the Role & Company
Nameless Ventures is hiring a Data Engineer in Dubai, United Arab Emirates. The role sits inside a Software Engineering team that’s actively expanding its footprint in the region. Career-wise, joining a growing team beats a static one; there’s more room to shape scope early. You’ll cover the core Data Engineer remit, with room to pick up adjacent work as the team matures. Dubai remains a strong market for software engineering professionals; salaries have held up and tax structure keeps take-home meaningful. Anyone at the mid-level should read this as a chance to broaden scope; anyone earlier in their career gets meaningful work sooner than most training paths would offer.
Key Requirements
- Demonstrated strong commercial experience with
- $5,500 USD per month, depending on experience + discretionary annual bonus
- candidates must be based within GMT+4
Job Description
Data Engineer β Fully Remote- within GMT+4 timezones!
Iβm currently partnering with a fast-growing B2B SaaS iGaming company building
Data Engineer to join their team on a fully remote basis .
This is a hands-on data engineering role working across real-time, near-real-time, and batch data pipelines , supporting high-scale products across personalisation, recommendation, fraud detection, and AI/ML use cases . π οΈ What Youβll Be Doing: β’ Build and keep up scalable batch, near-real-time, and real-time data pipelines . β’ Build production-grade pipelines using
Kafka, Spark, Databricks, PySpark, and Airflow . β’ Design and optimise data models and distributed processing workflows for high-volume datasets. β’ Work closely with Data Science and Backend Engineering teams to support
ML, recommendation, personalisation, and fraud detection initiatives . β’ Improve testing, monitoring, reliability, and performance across production data systems. β’ Troubleshoot production issues and contribute to the ongoing stability and scalability of the data platform. β What Weβre Looking For: β’ 3+ yearsβ experience in Data Engineering or Software Engineering focused on data.
ATS Resume Tips for This Role
To get past Applicant Tracking Systems (ATS) for this Data Engineer opening, tailor your resume with the pointers below:
- Include these keywords verbatim in your Skills and Experience sections: Python, Docker, Kubernetes, CI/CD, SQL, JavaScript, React, Node.js, AWS, Git. ATS parsers match exact strings, not synonyms.
- Use a single-column layout. Two-column resumes break parsers β text gets scrambled or dropped.
- Save as .docx or standard .pdf (not scanned/image PDF). Avoid text boxes, headers, footers, graphics.
- Use standard section headings: Experience, Education, Skills, Certifications.
- Mirror the exact job title (Data Engineer) in your target role line where truthful.
- Quantify results with numbers, percentages, currency. Metrics improve ATS scoring and human review.
- Spell acronyms out once (e.g., Search Engine Optimization (SEO)) so parser catches both forms.
- Font: Arial, Calibri, or Times New Roman at 10-12pt. Fancy fonts can render as unreadable glyphs.
Top 10 Interview Questions for This Role
- Walk me through your background and why you’re interested in this role.
- Describe a challenging project you owned end-to-end. What was the outcome?
- Tell me about a time you disagreed with a stakeholder. How did you handle it?
- How do you prioritize when everything on your plate feels urgent?
- Explain how you’d design a system to handle 100k requests per minute.
- Walk through your debugging process on an intermittent production bug.
- What’s your approach to code reviews, both giving and receiving?
- Describe a technical trade-off you had to make and why.
- How do you keep up with new frameworks without chasing every trend?
- Talk through a time you refactored legacy code β what changed, what stayed?
How to Apply
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