Responsibilities

Job Description

Assistant Manager, Data & Analytics, IT(Bunkers & Technical - Singapore)

Responsible for designing and building dataproducts and analytical tools that support operational and commercial decision-makingacross the Bunkers and Technical domains.

The role combines hands-on data engineering andanalytics work with stakeholder-facing responsibilities. A strong focus remainson building scalable, practical solutions on top of Hafnia's Azure andDatabricks platform, while also enabling AI-ready data foundations.

Works closely with Technical and Bunkerstakeholders to understand workflows and translate them into structuredanalytical and data models that improve how fuel, vessel performance, and costdata is accessed and used in daily operations. Acts as a bridge between localSingapore business requirements and the Denmark-based global DnA team, ensuringalignment with shared data models, standards, and architectural principles.

Key Responsibilities

Business-FacingAnalytics (Bunkers & Technical)

• Partner with Technical and Bunker stakeholders to identify and define data-driven use cases
• Analyze fuel consumption, voyage performance, and bunker cost drivers
• Translate operational and commercial challenges into structured analytical models
• Provide data-driven insights and challenge business assumptions

Technical Data Ownership (Azure & Databricks)

• Work within Hafnia's Azure and Databricks data platform
• Develop, maintain, and optimize datasets, transformations, and data models
• Ensure data quality, consistency, and usability across business domains
• Collaborate with data engineers to ensure scalable and maintainable solutions

Data Product Development

• Design, build, and maintain dashboards and analytical tools (e.g. Power BI)
• Deliver scalable and reusable data products for business users
• Enable self-service analytics through well-structured and documented datasets
• Continuously improve data products based on business feedback and evolving needs

AI Enablement & MCP Contribution

• Contribute to the development of AI-ready data models within Bunkers and Technical domains
• Structure and prepare datasets for use in MCP (Model Context Protocol) and AI-driven solutions
• Define and document business logic and decision models for reuse in analytics and AI
• Collaborate with DnA and AI teams to ensure data products support reliable and explainable AI outcomes
• Support the transformation of business processes into structured, auditable data components

Global Collaboration

• Collaborate closely with the Denmark-based DnA team
• Ensure alignment with global data models, standards, and architectural principles
• Act as a bridge between local business requirements and global data strategy
• Contribute to the continuous evolution of Hafnia's Azure and Databricks platform

Day-to-DayActivities

• Engage with Bunker and Technical teams to understand operational and commercial challenges
• Analyze vessel performance and fuel consumption data using Databricks
• Query and transform data using SQL and Python in Azure environments
• Build and enhance dashboards and analytical tools
• Structure datasets for both analytics and AI use cases
• Collaborate with the Denmark DnA team on data models, standards, and priorities
• Participate in agile delivery within the DnA team

Focus Areas

• Improving access to Bunkers and Technical data and making it useful in daily operations
• Reducing manual processes through simple, reliable analytical tools
• Building scalable, reusable data products rather than one-off reporting
• Laying the foundation for AI-ready data models and MCP-driven use cases
• Enabling effective collaboration between Singapore business teams and the Denmark DnA team

Technical Skills

• SQL - advanced proficiency for data modelling, transformation, and analytics
• Python - core language for data engineering, scripting, and analysis
• Databricks - hands-on experience with data transformation, analysis, and data modelling (Unity Catalog, Jobs, Notebooks)
• Microsoft Azure - comfortable working across Azure data services and environments
• Data modelling - solid understanding of analytical data structures and modelling patterns
• Power BI - or similar visualization tools, for dashboards and self-service analytics
• Familiarity with distributed data processing, agile delivery, and modern analytics engineering practices is a plus
• Exposure to AI / ML or data-driven automation initiatives is an advantage

Business Understanding

• Understanding of fuel economics, vessel operations, or trading environments is an advantage
• Ability to translate business requirements into structured data and analytical models
• Strong analytical mindset with a clear focus on value creation

AI & Data Thinking

• Understanding of how structured data enables AI and automation
• Ability to define and document business logic for analytical and AI use cases
• Interest in building AI-ready data foundations, not just reporting

Collaboration & Communication

• Strong communication skills in both English and Danish, written and verbal
• Ability to work effectively across geographies, particularly between Singapore and Denmark
• Comfortable engaging both technical and non-technical stakeholders
• Ability to operate in a dynamic and evolving environment

Required Experience

• 2 to 5 years of experience in a Data & Analytics or IT function
• Experience in shipping, bunkers, commodities, energy, or similar industries
• Hands-on experience with Azure and Databricks environments
• Experience working across business and technical teams
• Experience collaborating with distributed or global teams
• Experience supporting or enabling data for AI or advanced analytics use cases is an advantage

Qualifications

• Degree in IT, Data Analytics, Computer Science, or a Business-IT hybrid discipline
• Preference for candidates with combined business and technology education
• Experience in maritime or shipping-related data domains
• Familiarity with distributed data processing within Databricks
• Experience working in agile environments
• Exposure to AI, machine learning, or data-driven automation initiatives

Mindset & Culture Fit

• Eager to learn fast, comfortable operating in a rapidly evolving tech and AI landscape
• Genuinely passionate about building data products
• Embraces AI as a force multiplier - uses LLMs, copilots, and agentic tools to move faster, automate the mundane, and focus on what matters
• Thrives in a hands-on, low-bureaucracy environment where ownership and initiative are valued over titles