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Master Works is seeking an experienced Data Engineer to design, build, and operate scalable data platforms in Riyadh, Saudi Arabia. You will develop reliable data infrastructure, reusable self-service pipelines, and modern lakehouse capabilities across warehouses and lakes, while ensuring data quality and governance.
The role demands strong SQL and programming skills (Python/Java/Scala), plus hands-on experience with data orchestration tools and IaC.
Riyadh, Saudi Arabia — On-site / Client Site
Master Works is seeking an experienced Data Engineer to support the development and operation of scalable data platforms in Riyadh, Saudi Arabia. The role focuses on building reliable data infrastructure, reusable self-service pipelines, and modern data platform capabilities across data warehouses, data lakes, and lakehouse environments.
The successful candidate will be responsible for data pipeline development, orchestration, monitoring, observability, data quality, system integration, performance optimization, security, governance, and compliance. The position requires strong programming and SQL capabilities, combined with practical experience in enterprise-scale data engineering and platform architecture.
This opportunity provides strong potential for career growth and professional development through exposure to large-scale data systems, modern data architecture, Infrastructure-as-Code, orchestration technologies, and enterprise data governance. Candidates can further develop their expertise through relevant data engineering certifications, technical training, cloud technologies, and advanced data platform skills.
The job posting does not specify a salary or compensation package.
This role offers opportunities for career progression and professional development within enterprise data engineering and data platform environments. Professionals can expand their capabilities through technical training, data engineering certifications, cloud technologies, Infrastructure-as-Code, orchestration platforms, and advanced lakehouse and data architecture practices.