Professional Data Engineer
Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Sep 29, 2026.
Property Finder 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. At its core is a clear and powerful purpose: To change living for good in the region.
Founded on the value of great ambitions, Property Finder connects millions of property seekers with thousands of real estate professionals every day. The platform offers a seamless and enriching experience, empowering both buyers and renters to make informed decisions. Since its inception in 2007, Property Finder has evolved into a trusted partner for developers, brokers, and home seekers. As a lighthouse tech company, it continues to create an environment where people can thrive and contribute meaningfully to the transformation of real estate in MENA.
Position Summary: We are seeking a Professional Data Engineer to join our dynamic team, where you will play a crucial role in developing and maintaining robust data solutions.
As a Professional Data Engineer, you will collaborate with data science, business analytics, and product development teams to deploy cutting-edge techniques and utilise best-in-class third-party products.
The Data team operates with engineering precision, prioritising security, privacy, and regulatory compliance in every initiative.
As a Professional Data Engineer, you will contribute to the team's commitment to utilising the latest tools and methodologies, ensuring that our data solutions align with industry best practices.
Our Tech Stack: Languages: SQL & Python Pipeline orchestration tool: Dagster (Legacy: Airflow) Data stores: Redshift, Clickhouse Platforms & Services: Docker, Kubernetes PaaS: AWS (ECS/EKS, DMS, Kinesis, Glue, Athena, S3 and others.) ETL: FiveTran & DBT for transformation IaC: Terraform (with Terragrunt) GenAI: Bedrock, LangChain, LLMs Key Responsibilities: Develop and maintain ETL pipelines using SQL and/or Python.
Use tools like Dagster/Airflow for pipeline orchestration Collaborate with cross-functional teams to understand and deliver data requirements. Ensure a consistent flow of high-quality data using stream, batch, and CDC processes. Use data transformation tools like DBT to prepare datasets to enable business users to self-service.
Ensure data quality and consistency in all data stores. Monitor and troubleshoot data pipelines for performance and reliability. Essential Experience: 5+ years of experience as a data engineer. Proficiency in SQL. Experience with modern cloud data warehousing, data lake solutions like Snowflake, BigQuery, Redshift, Azure Synapse.
Experience with ETL/ELT, batch, streaming data processing pipelines. Excellent ability to investigate and troubleshoot data issues, providing fixes and proposing both short and long-term solutions. Knowledge of AWS services (like S3, DMS, Glue, Athena, etc.) Familiar with dbt or other data transformation tools. Familiarity with GenAI, and how to leverage LLMs to resolve engineering challenges Other Desired Experience: Experience with AWS services and concepts (like EC2, ECS, EKS, VPC, IAM, etc). Familiar with Terraform and Terragrunt.
Experience with Python Experience with orchestration tools like Dagster, Airflow, AWS Step functions, etc. Experience with pub-sub, queuing, and streaming frameworks such as AWS Kinesis, Kafka, SQS, SNS. Familiar with CI/CD pipelines and automation.
Our promise to talent
At Property Finder, we believe talent thrives in an environment where you can be your best self. Where you are empowered to create, elevate, grow, and care. Our team is made up of the best and brightest, united by a shared ambition to change living for good in the region. We attract top talent who want to make an impact. We firmly believe that when our people grow, we all succeed.
Property Finder Guiding Principles
Think Future First
Data Beats Opinions, Speed Beats Perfection
Optimise for Impact
Act Like An Owner
The Biggest Risk is Taking no Risk at All