Senior Architect Data
Listed on 2026-09-05
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IT/Tech
Data Engineering, Data Warehousing, Cloud Computing: Infrastructure & Operations
About the Role
We are seeking a highly experienced Senior Architect Data to join our team in Riyadh In this role you will define and drive the end-to-end data architecture strategy design scalable data platforms and lead the implementation of modern data solutions to support business objectives
ResponsibilitiesDesign and implement robust scalable data architectures and frameworks Develop and maintain enterprise data models and data dictionaries Lead the design and deployment of datalake solutions to ingest store and process large volumes of data Architect and optimize Databricks-based data pipelines and ETL processes Define and enforce data architecture standards best practices and governance policies Collaborate with cross-functional teams to translate business requirements into technical designs Evaluate and integrate GCP services to support data storage processing and analytics Mentor and guide junior data engineers and architects on architecture patterns and technologies
Position Details- Position Title Senior Architect Data
- Location Riyadh Saudi Arabia
- Industry Information Technology IT Software Experience Required 9 years
- 9-12 years of experience in data architecture or related roles
- Proven expertise in data architecture design and implementation
- Strong experience with data modelling techniques and tools
- Hands-on experience designing and managing enterprise datalake solutions
- Extensive experience with Databricks and Spark-based pipelines
- Deep knowledge of Google Cloud Platform data services (Big Query, Dataflow, Pub/Sub, Cloud Storage)
- Solid understanding of ETL/ELT processes and data integration patterns
- Excellent communication, leadership, and stakeholder management skills
- Google Cloud Professional Data Engineer or equivalent certification
- Databricks Certified Data Engineer credential
- Experience with additional cloud platforms (AWS, Azure)
- Familiarity with real-time data processing technologies (Kafka, Pub/Sub)
- Background in machine learning infrastructure and MLOps
- Experience implementing data governance and metadata management solutions
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