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 critical role involves 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 Accountabilities / Responsibilities:
• A. Data Engineering and Integration: Design and develop data pipelines to ingest data from operational systems, build ETL/ELT processes, integrate structured and unstructured data sources, and ensure seamless data flow between operational systems and analytics platforms.
• B. Data Architecture and Management: Develop and maintain scalable data models, support implementation of data warehouse / data lake architecture, optimize database performance, and maintain metadata, data lineage, and documentation standards.
• C. Data Quality and Governance: Ensure data accuracy, consistency, and completeness, implement data validation, monitoring, and quality control mechanisms, collaborate with IT and Data Science teams to enforce data governance standards, and support compliance with data security and regulatory requirements.
• D. Analytics Enablement: Prepare clean, structured datasets for use in dashboards and analytics tools, enable data availability for key use cases, and support Data Science team in model development and deployment.
• E. Performance and Continuous Improvement: Identify opportunities to automate manual data processes, improve pipeline efficiency, reduce data latency, and support scalability of data infrastructure as business needs evolve.

• Skills / Attributes: Strong SQL and data modelling 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.
• 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 related field.
• Working Conditions: Within the terminal – both indoor and outdoor.
• Competencies: Analytical Thinking, Problem Solving, Collaboration & Influence, Results Orientation, Innovation, Data-Driven Decision Making, Integrity, Dynamic