Data Engineer – Build Scalable Data Pipelines

About the role

Design, build, and maintain batch and streaming data pipelines that power fraud detection, recommendation engines, personalisation, and AI/ML products. Work with technologies such as Kafka, Spark (Databricks), Airflow, and Python in a collaborative, engineering‑driven environment.

Key responsibilities

• Develop and operate scalable data pipelines for both batch and real‑time processing.
• Integrate and manage Kafka streams, Spark jobs on Databricks, and Airflow workflows.
• Collaborate with data scientists and backend engineers to ensure high‑quality, reliable data delivery.
• Monitor pipeline performance, implement testing, and maintain reliability.
• Contribute to continuous improvement of the data platform and related tooling.

Required profile

• 3+ years of experience in Data Engineering or Software Engineering (Data).
• Strong Python programming skills, including experience with PySpark.
• Hands‑on experience with Kafka and stream processing (Flink is a plus).
• Experience with Spark on Databricks and orchestration tools such as Airflow.
• Solid knowledge of SQL, data modelling, and relational databases.
• Familiarity with Docker, Kubernetes, feature stores, MLOps or high‑scale SaaS environments is a plus.

Required skills

• Python
• PySpark
• Kafka
• Spark (Databricks)
• Airflow
• SQL
• Data modelling
• Relational databases

What we offer

• Salary AED 15,000–18,000 per month plus performance‑based bonus.
• Comprehensive medical insurance.
• Annual flight allowance and visa sponsorship.
• Annual leave entitlement and learning & conference budget.
• Hybrid working model (≈3 days per week in the Dubai office) with a distributed team across Dubai and Europe.