Data Engineer

About the Role

We are collaborating with a prominent, well-established family conglomerate in Saudi Arabia to recruit a skilled Data Engineer. Within this diversified business group, data is the lifeblood that fuels operations across all sectors, and the infrastructure supporting it must meet the highest standards. This is a prime opportunity to engage with large-scale data challenges that have a tangible impact, all within an organisation that is significantly investing in its technological capabilities.

This position is ideal for an engineer who prioritizes reliability, data integrity, and the development of robust pipelines that the broader business can rely upon. The Data Engineer will play a pivotal role in designing, constructing, and maintaining scalable data pipelines that facilitate the seamless movement, transformation, and delivery of data across multiple business units within the Group. Responsibilities include owning the development and continuous improvement of the data platform, ensuring its reliability and performance in both batch and streaming environments. Collaboration with data scientists, analysts, and AI engineers will be essential to guarantee that clean, well-structured data is accessible precisely when and where it is required.

The role also involves implementing robust data quality frameworks, rigorous testing practices, and observability tooling to maintain the trustworthiness of pipelines in production. Additionally, the Data Engineer will contribute to critical data modelling and architecture decisions, ensuring the platform evolves in tandem with the Group’s growth and increasing complexity. Supporting the Group’s AI and machine learning initiatives by designing data infrastructure that powers model training, feature engineering, and inference pipelines will be a key responsibility.

Your Qualifications

• 3 to 5 years of hands-on experience in data engineering or a closely related field, with a proven track record of delivering scalable data solutions.
• Strong proficiency in Python and SQL, coupled with a deep understanding of software engineering principles as they apply to data workflows.
• Demonstrated experience with cloud-based data platforms such as Snowflake, BigQuery, or Redshift, and the ability to leverage their capabilities effectively.
• Proven expertise in building and maintaining both batch and streaming pipelines using frameworks like Apache Spark, Kafka, or Airflow.
• Familiarity with modern data transformation tools such as dbt, along with a solid grasp of contemporary data stack practices.
• Ability to thrive in a complex, multi-business-unit environment where data ownership, governance, and cross-functional collaboration are paramount.