Data Engineer – Scalable Data Platforms

About the role

The Data Engineer will design, build, and operate scalable, resilient data platforms that enable high‑impact analytics and decision‑making. Working closely with product, analytics, and engineering teams, you will prototype, deliver, and run reliable data pipelines and big‑data services in production.

Key responsibilities

• Design and develop services for large‑scale ingestion, storage, and management across RDBMS, NoSQL, logs, and event streams.
• Build and operate robust batch and streaming pipelines using Apache NiFi, Kafka, Spark, Flink, and Airflow.
• Implement change‑data‑capture, OLAP, dimensional and lake‑house models for analytics and AI.
• Ensure pipelines are deployable, observable, and meet data SLAs, with quality checks, lineage, documentation and governance.
• Collaborate with product teams, third‑party providers and Data Scientists on integrations and dataset preparation.
• Participate in sprint planning, advise on emerging data technologies, and protect sensitive data in line with security policies.

Required profile

• 3‑5 years of professional experience as a Data Engineer or Big Data Engineer.
• Bachelor’s degree in Computer Science, Software Engineering or related field (preferred).
• Strong programming and scripting skills in Python, Scala or Java and advanced SQL.
• Excellent English; Arabic is an advantage.

Required skills

• Data pipelines: Apache NiFi, Kafka, Spark, Flink, Airflow.
• Distributed architectures, CDC (e.g., Debezium), OLAP design.
• Storage & messaging: MinIO/S3, Kafka; data formats: Avro, Parquet, ORC.
• Programming: Python, Scala, Java; advanced SQL.
• Agile delivery, Git version control.