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Known multinational brand plus common senior data title but specialized enterprise modelling skills.
Core data engineering skills transfer across industries, but enterprise modelling and domain context increase sensitivity.
Explicit 8+ years plus mandatory enterprise data modelling, cloud platforms, and specific tools.
Lead design, governance, and continuous evolution of enterprise data models and data products ensuring alignment with architecture standards and business needs.
Design and deliver reliable, high-performance data engineering solutions including ingestion, transformation, integration, and orchestration pipelines across cloud platforms.
Collaborate with Data Engineers, Solution Engineers, and Business Stakeholders to translate requirements into governed, AI-ready data products following Data-as-a-Product principles and governance practices.
8+ years of experience in enterprise data modelling and data engineering for large-scale data warehouses and enterprise data products on modern cloud platforms.
Bachelor's degree in Computer Science, IT, Data Analytics, Engineering, or related field; Master's degree preferred.
Strong expertise in conceptual, logical, physical data models, dimensional modelling, Data Vault, and enterprise data architecture standards.
Hands-on experience with Snowflake, Databricks, SQL, Matillion, dbt, and Power BI including building scalable data pipelines and integration solutions.
Demonstrated ability to lead technical design and data model reviews and enforce enterprise-wide modelling, engineering, and governance best practices.
Experience with Data-as-a-Product operating models and creating AI-ready data platforms to support advanced analytics and GenAI initiatives.
Strong collaboration skills evidenced by working with multi-disciplinary teams (Solution Engineers, Architects, Business) to develop scalable data products and enforce governance.