Data Engineering Specialist

About the Role

Saudi Aramco is seeking a Data Engineering Specialist to join the Downstream Global Optimizer (GO) team. This full-time role focuses on driving commercial optimization across Saudi Aramco’s integrated downstream value chain, including domestic and international refining assets. The GO team identifies and captures optimization opportunities to enhance system netback and deliver shareholder value.

Role Context and Impact

The Data Engineering Specialist will design, develop, and maintain scalable data platforms that power the iGO (intelligent Global Optimizer) ecosystem. This work ensures seamless integration of structured and unstructured data, enables high-performance analytics, and provides reliable foundations for optimization models, machine learning pipelines, and enterprise reporting. The specialist will build and maintain the data infrastructure that supports data scientists, designing and implementing scalable data pipelines, ensuring data quality, and managing data storage solutions. Collaboration with data scientists and other teams is essential to provide the necessary data infrastructure for advanced analytics and machine learning models.

Key Responsibilities

• Design and implement data architectures and efficient ETL (Extract, Transform, Load) processes to move and transform data from various sources into a format suitable for analysis.
• Ensure the accuracy, completeness, and consistency of data by implementing data validation and cleansing processes.
• Architect and manage data storage solutions, including data lakes and warehouses, to meet organizational needs.
• Collaborate with data scientists and other stakeholders to understand data requirements and provide appropriate data solutions.
• Optimize data pipelines and architectures for scalability and performance, ensuring efficient handling of large volumes of data.
• Maintain thorough documentation of data systems, pipelines, and processes for clarity and continuity.

Qualifications and Experience

• Bachelor’s degree in Computer Science, Data Engineering, Software Engineering, or a related field from a recognized institution. A Master’s or advanced degree is preferred.
• A minimum of 10 years of experience in data engineering, data architecture, or enterprise data platform development, including at least 5 years in designing and managing enterprise-grade data pipelines.
• Strong technical expertise in programming languages such as Python, SQL, and Scala, with experience in data engineering frameworks like Apache Spark, Kafka, Airflow, and Flink.
• Proven experience building data lakes, data warehouses, and ETL/ELT pipelines for large-scale, heterogeneous datasets.
• In-depth knowledge of cloud platforms (AWS, GCP, Azure) and distributed data processing tools (*, Databricks, Cloudera, Snowflake).
• Hands-on experience with data governance, metadata management, and data quality frameworks.
• Ability to work effectively in complex, cross-functional environments, translating business needs into scalable data architectures.
• Strong communication skills to articulate technical designs to stakeholders and mentor junior engineers.

Preferred Skills and Certifications

• Familiarity with industrial/energy sector data ecosystems (*, OT/IT systems, SCADA, ERP, market data).
• Certifications in cloud platforms (AWS/GCP/Azure) or data engineering (*, Google Professional Data Engineer, AWS Big Data Specialty).