Data Engineering & Warehousing Engineer

About the role

We are looking for a highly skilled Data Engineering & Warehousing Engineer to design, develop, and maintain scalable data platforms and enterprise data warehouse solutions. The role involves building robust ETL/ELT pipelines, integrating diverse data sources, and supporting analytics and BI initiatives for our Riyadh office.

Key responsibilities

• Design, develop, and optimise scalable ETL/ELT pipelines for both structured and unstructured data.
• Build and maintain enterprise data warehouses, data lakes, and modern cloud‑based data platforms.
• Develop real‑time and batch data processing solutions using Spark, Kafka and related technologies.
• Integrate data from multiple internal and external sources while ensuring data quality, governance and security.
• Collaborate with data scientists, BI developers and business stakeholders to meet analytical requirements.
• Optimise data storage, query performance and pipeline reliability.
• Implement monitoring, security and governance best practices.
• Troubleshoot and resolve data pipeline and platform issues.
• Participate in architecture discussions and contribute to data platform modernisation initiatives.

Required profile

• Bachelor's degree in Computer Science, IT, Data Engineering or a related field.
• 3–11 years of professional experience in data engineering, data warehousing or big data technologies.
• Strong analytical and problem‑solving abilities.
• Experience working in Agile/Scrum environments.

Required skills

• Cloud platforms: Google BigQuery, Dataflow, Dataproc, Pub/Sub; Azure Synapse, Azure Data Factory; Amazon Redshift, AWS Glue.
• Data processing: Apache Spark, Apache Kafka.
• Data transformation/orchestration: dbt, Oracle Data Integrator (ODI).
• Databases & warehousing: Oracle, PostgreSQL, advanced SQL, performance tuning.
• Programming/scripting: Python, SQL.
• Data modelling, dimensional modelling, data governance, metadata management.
• CI/CD pipelines, Infrastructure as Code (IaC), Docker, Kubernetes (preferred).