Data and ML Platform Engineer

Data and ML Platform Engineer

The Data and ML Platform Engineer is responsible for designing, building, and maintaining scalable data pipelines and architecture that ensure reliable, high-quality data availability across port operations. This role is 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.

Key Responsibilities:

• Data Engineering and Integration: Design and develop data pipelines to ingest data from operational systems, build ETL/ELT processes, and integrate structured and unstructured data sources. Ensure seamless data flow between operational systems and analytics platforms.
• Data Architecture and Management: Develop and maintain scalable data models, support data warehouse/data lake implementation, optimize database performance, and maintain metadata, data lineage, and documentation standards.
• Data Quality and Governance: Ensure data accuracy, consistency, and completeness, implement data validation and monitoring mechanisms, and collaborate with teams to enforce data governance standards.
• Analytics Enablement: Prepare clean, structured datasets for dashboards and analytics tools, enable data availability for key use cases, and support Data Science team in model development and deployment.
• Performance and Continuous Improvement: Identify automation opportunities, improve pipeline efficiency, reduce data latency, and support scalability of data infrastructure.

Required Experience: 3-6 years in data engineering or backend data systems, with 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 modeling expertise, proficiency in Python for data engineering, experience working with APIs and large datasets, understanding of cloud platforms (Azure preferred), strong problem-solving and system design skills.

Competencies: Analytical Thinking, Problem Solving, Collaboration & Influence, Results Orientation, Innovation, Data-Driven Decision Making, Integrity, Dynamic.

Working Conditions: Within the terminal – both indoor and outdoor.

Reporting To: Data Science Senior Manager