The company is the leading property portal in the Middle East and North Africa (MENA) region, dedicated to shaping an inclusive future for real estate while spearheading the region’s growing tech ecosystem. Our mission is to change living for good in the region by connecting millions of property seekers with thousands of real estate professionals every day. Since 2007, the company has evolved into a trusted partner for developers, brokers, and home seekers, creating an environment where people can thrive and contribute meaningfully to the transformation of real estate in MENA.
Ready to apply for roles like this?
Unlock the company name and direct application link. Subscribers get instant access to fresh jobs across Dubai, Abu Dhabi and Riyadh, many with visa support.
Unlock employer & apply directly
We are looking for a Data Engineer to build reliable, scalable data pipelines and contribute to the core data ecosystem that powers analytics, AI/ML, and emerging Generative AI use cases. You will work closely with senior engineers and data scientists to deliver high-quality pipelines, models, and integrations that support business growth and internal AI initiatives.
Key Responsibilities:
- Core Engineering: Build and maintain batch and streaming data pipelines with emphasis on reliability, performance, and cost efficiency. Develop SQL, Python, and Spark/PySpark transformations for analytics, reporting, and ML workloads.
- GenAI & Advanced Data Use Cases: Create data flows that support GenAI workloads and collaborate with ML/GenAI teams for high-quality training datasets.
- Collaboration & Delivery: Work with various teams to translate data requirements and maintain strong data quality and documentation standards.
- Professional Growth & Team Contribution: Demonstrate ownership of components of the data platform and contribute to team learning through sharing knowledge.
Impact of the Role:
You will extend and strengthen the data foundation that powers analytics, AI/ML, and GenAI initiatives across the company, improving data availability and performance.
Tech Stack:
- Languages: Python, SQL, Java/Scala
- Streaming: Kafka, Kinesis
- Data Stores: Redshift, Snowflake, ClickHouse, S3
- Orchestration: Dagster (Airflow legacy)
- Platforms: Docker, Kubernetes
- AWS Services: DMS, Glue, Athena, ECS/EKS, S3, Kinesis
- ETL/ELT: Fivetran, dbt
- IaC: Terraform + Terragrunt
Desired Qualifications:
- 5+ years of experience as a Data Engineer
- Strong SQL and Python skills; understanding of Spark/PySpark
- Experience with cloud-based data warehouses and data lake architectures
- Familiarity with orchestration tools (Dagster, Airflow)
- Exposure to Generative AI workflows or willingness to learn
Preferred Experience:
- Experience in the Real Estate sector
- Familiarity with ETL tools, real-time analytics, and BI tools
- Experience with Terraform & Terragrunt; knowledge of GCP or Google Analytics is a plus.
Work Conditions:
- Full-time, on-site position
Language Requirements:
- Proficient in English (specific language requirements not mentioned, but an understanding of regional languages is a plus).
