Senior Data Modeler

CONTEXT

Imagine a bustling crossroads of global commerce, a nexus where goods and information flow continuously. Our client, a major player in its sector, is a vast ecosystem encompassing ship movements, cargo tracking, environmental monitoring, and intricate financial transactions. This generates an enormous, ever-growing volume of data – a treasure trove waiting to be unlocked. However, like many complex organizations, this data is often siloed, inconsistent, or not fully leveraged for strategic decision-making.

The challenge and the opportunity lie in transforming this raw data into a cohesive, intelligent resource. Our client is embarking on a profound digital transformation journey, aiming to optimize every facet of its operations – from logistics efficiency and predictive maintenance to environmental sustainability and innovative service delivery – through data-driven insights. As a Senior Data Modeler, you will be the architect of this transformation, building the robust and intuitive data models that form the very bedrock of this new, intelligent infrastructure.

ACTIVITIES

• Design, develop, and maintain conceptual, logical, and physical data models for various business domains, ensuring scalability, flexibility, and adherence to industry best practices.
• Collaborate extensively with business stakeholders and data analysts to thoroughly understand data requirements, translating complex business needs into precise data definitions and structures.
• Act as a proactive discussion partner, challenging assumptions and proposing optimal data usage strategies to maximize the value extracted from available data sources.
• Optimize existing data models and structures to improve performance, data quality, and accessibility across the enterprise.
• Define and enforce clear data definitions, metadata standards, and data governance policies within the Data & Analytics team and across business units.
• Coach and mentor business users on data literacy, data modeling concepts, and effective data utilization, fostering a data-aware culture.
• Work closely with data engineers and ETL/ELT developers to ensure seamless integration and transformation of data into the modeled structures.
• Participate in data governance initiatives, contributing to the overall data strategy and ensuring compliance with data quality and security standards.

EXPECTED ACHIEVEMENTS

• A unified, accessible, and high-quality data landscape that serves as a single source of truth for critical business operations and strategic decisions.
• Significantly improved data quality and consistency, leading to more reliable reporting and analytics across all departments.
• Empowered business users who possess a deeper understanding of data and can independently leverage data for insights and decision-making.
• Faster and more accurate data-driven decision-making processes, directly contributing to enhanced operational efficiency, cost savings, and the identification of new strategic opportunities.
• A well-documented and governed data environment that supports future growth and technological advancements, positioning the organization as a leader in data innovation within its sector.

ENVIRONMENT

• Data Modeling: ORM2, NIAM, FCO-IM, Dimensional Modeling, Relational Modeling
• Databases & Warehousing: SQL, Data Warehousing concepts, Data Lake architectures
• Tools & Technologies: DBT (Data Build Tool), BPMN (Business Process Model and Notation)
• Methodologies: Agile, Scrum, Data Governance frameworks (e.g., DAMA-DMBoK)
• Cloud Platforms (exposure a plus): Azure, AWS, GCP
• Additional: Master Data Management (MDM) principles, Data Quality tools, BI/Analytics platforms (e.g., Power BI, Tableau)