Professional Data Engineer

at  Property Finder

Founded by Michael Lahyani in 2005 as a magazine (Al Bab World), Property Finder today is a single technology platform and brand across multiple countries in the MENA region. We offer the most advanced tools and best-in-class user experience for homeseekers, real estate brokers, and developers. Property Finder’s most recent valuation secures our status among the Middle East’s emerging unicorns, affirming a growth-oriented identity.
Over the years, we’ve expanded our operations to Bahrain, Egypt, Qatar, Saudi Arabia, and secured a strategic shareholding in Hepsiemlak, the leading property portal in Turkey. With over 600+ dedicated people in 6 regional offices, we facilitate more than 14 million monthly visits across our platforms, solidifying our position as a regional powerhouse in the proptech space.
As the pioneering portal for homeseekers in the region, we are on a mission to motivate and inspire people to live the life they deserve.

POSITION SUMMARY:

We are in search of a Professional Data Engineer to enhance our data engineering capabilities.
In this role, you will support junior team members, driving the development and maintenance of sophisticated data solutions.
Beyond that, you will contribute in building and maintaining the infrastructure necessary for data engineering processes.
Collaborating with cross-functional teams, you will contribute to building self-service data layers and provide crucial insights to align data architecture with broader business strategies. Your contribution towards innovative solutions and ensuring the highest standards of data quality.

ESSENTIAL EXPERIENCE:

• 7+ years of experience as a data engineer
• Proficiency in SQL and Python
• Experience with modern cloud data warehousing, data lake solutions like Snowflake, BigQuery, Redshift.
• Experience with ETL/ELT, batch, streaming data processing pipelines.
• Experience with AWS services (like S3, DMS, Glue, Athena, EKS, etc.)
• Proven experience with data warehousing and dimensional data modelling guidelines and best practices
• Familiar with ETL tools like FiveTran, DBT, Airbyte, etc
• Experience with orchestration tools like Dagster, Airflow, AWS Step functions, etc.
• Knowledge of CI/CD pipelines and automation.

OTHER DESIRED EXPERIENCE:

• Experience with Terraform and Terragrunt.
• Experience with data stores like MySQL, MongoDB, DynamoDB, Aurora.
• Experience with pub-sub, queuing, and streaming frameworks such as AWS Kinesis, Kafka, SQS, SNS.
• Experience in real time processing engines like Apache Flink, Apache Spark etc.
• Familiar with BI tools like Tableau, QuickSight, Tableau, PowerBI, MicroStrategy, etc
• Familiar with Tagging and tracking tools like Snowplow, Tealium,Segment.io etc
• Experience with Realtime analytics solutions like Clickhouse, Rockset, Pinot, or Druid.
• Experience with GCP and Google Analytics.

• Design and implement complex ETL solutions for large datasets.
• Optimise and fine-tune SQL and/or Python code for performance.
• Design and maintain data models for efficient storage and retrieval.
• Troubleshoot and resolve issues related to data pipeline performance.
• Build and maintain self-service datasets to accelerate data democratization efforts.
• Contribute to the initiatives for managing and optimizing infrastructure.
• Implement best practices for version control and collaboration in Terraform.