Data Engineer

Data Engineer – Fully Remote- within GMT+4 timezones!

I’m currently partnering with a fast-growing B2B SaaS iGaming company building AI-powered products for the Gaming industry, who are looking for a 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 .

🛠️ What You’ll Be Doing:

• Build and maintain scalable batch, near-real-time, and real-time data pipelines .

• Develop production-grade pipelines using Kafka, Spark, Databricks, PySpark, and Airflow .

• Design and optimise data models and distributed processing workflows for high-volume datasets.

• Work closely with Data Science and Backend Engineering teams to support ML, recommendation, personalisation, and fraud detection initiatives .

• Improve testing, monitoring, reliability, and performance across production data systems.

• Troubleshoot production issues and contribute to the ongoing stability and scalability of the data platform.

✅ What We’re Looking For:

• 3+ years’ experience in Data Engineering or Software Engineering focused on data.

• Strong Python and PySpark experience.

• Strong hands-on experience with Kafka and stream processing .

• Strong commercial experience with Databricks .

• Experience with Apache Airflow or similar orchestration tools .

• Strong SQL, data modelling, and relational database experience.

• Strong software engineering fundamentals, including testing, CI/CD, monitoring, and production reliability .

• Exposure to Flink, ML pipelines, MLOps, feature stores, GenAI, Docker, Kubernetes, or iGaming is a bonus.

🎁 Package & Benefits:

💰 $4,500-$5,500 USD per month, depending on experience + discretionary annual bonus

🏠 Fully remote role - candidates must be based within GMT+4

🏖️ 30 days annual leave

⚡ 3-stage interview process – urgent hire

If this sounds like you, please apply below!