Data and ML Platform Engineer
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Key skills for this role
About the Role
Red Sea Gateway Terminal is looking for a Data and ML Platform Engineer to design, build, and maintain scalable data pipelines and architecture for port operations. The role involves integrating operational systems like Navis N4 and IoT platforms to support analytics and AI-driven decision-making.
Key Skills for This Role
Responsibilities
- Design and develop data pipelines to ingest data from operational systems including Navis N4, equipment systems, and enterprise platforms
- Build ETL/ELT processes for batch and near real time data ingestion
- Integrate structured and unstructured data sources across terminal operations
- Develop and maintain scalable data models to support reporting and analytics
- Support implementation of data warehouse / data lake architecture
- Optimize database performance and ensure efficient query execution
- Maintain metadata, data lineage, and documentation standards
- Ensure data accuracy, consistency, and completeness across datasets
- Implement data validation, monitoring, and quality control mechanisms
- Prepare clean, structured datasets for use in dashboards and analytics tools such as Microsoft Power BI
- Enable data availability for key use cases such as crane utilization tracking, vessel turnaround analysis, and yard optimization
- Support Data Science team in model development and deployment
Requirements
- 3–6 years of experience in data engineering or backend data systems
- Bachelor’s or master’s degree in computer science, Data Engineering, Information Systems, or a related field
- Strong SQL and data modelling expertise
- Proficiency in Python for data engineering (ETL, pipelines)
- Experience working with APIs and large datasets
- Understanding of cloud platforms (Azure preferred)
- Strong problem solving and system design skills
- Experience working with operational or industrial datasets preferred
Full Job Posting
Purpose of the Job
- To design, build, and maintain scalable data pipelines and architecture that enable reliable, high quality data availability across port operations.
- The role will be critical in integrating operational systems such as Navis N4 Terminal Operating System, IoT platforms, and enterprise systems to support analytics, reporting, and AI driven decision making across Group RSGT.
Required Experience
- 3–6 years of experience in data engineering or backend data systems.
- Experience working with operational or industrial datasets preferred.
- Proven ability to build and maintain data pipelines in production environments.
Education Requirements
- Bachelor’s or master’s degree in computer science, Data Engineering, Information Systems, or a related field.
Skills / Attributes
- Strong SQL and data modelling expertise.
- Proficiency in Python for data engineering (ETL, pipelines).
- Experience working with APIs and large datasets.
- Understanding of cloud platforms (Azure preferred).
- Strong problem solving and system design skills.
Key Accountabilities / Responsibilities
- Design and develop data pipelines to ingest data from operational systems including Navis N4, equipment systems, and enterprise platforms.
- Build ETL/ELT processes for batch and near real time data ingestion.
- Integrate structured and unstructured data sources across terminal operations.
- Ensure seamless data flow between operational systems and analytics platforms.
- Develop and maintain scalable data models to support reporting and analytics.
- Support implementation of data warehouse / data lake architecture.
- Optimize database performance and ensure efficient query execution.
- Maintain metadata, data lineage, and documentation standards.
- Ensure data accuracy, consistency, and completeness across datasets.
- Implement data validation, monitoring, and quality control mechanisms.
- Collaborate with IT and Data Science teams to enforce data governance standards.
- Support compliance with data security and regulatory requirements.
Competencies
- Analytical Thinking
- Problem Solving
- Collaboration & Influence
- Results Orientation
- Innovation
- Data Driven Decision Making
- Integrity
- Dynamic
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