Data Architect/Modeller

Required Skills & Qualifications:

• Proven experience in dimensional data modeling, data lake architecture, and enterprise data integration.
• Strong knowledge of OneStream, Hyperion, and financial systems such as Oracle EBS or equivalent.
• Hands-on expertise with Azure Data Lake, Power BI, and cloud-based analytics environments.
• Proficient in ETL/ELT development, data transformation, and scripting (SQL, Python, etc.).
• Solid understanding of metadata management, data governance, and lineage tracking.
• Experience implementing data security, encryption, and compliance controls.
• Familiarity with building and maintaining data marts for self-service analytics.
• Excellent communication and stakeholder engagement skills across business and technical teams.
• Bachelor’s or master’s degree in computer science, Information Systems, Data Engineering, or related field.

Must Haves:

• Architect and develop a robust dimensional data model across OneStream, Hyperion, Oracle EBS, HCM, and Work brain systems. – Finance within a company
• Design and optimize fact and dimension tables, data marts, and calculated metrics within the Azure Data Lake to support analytical and operational reporting.
• Lead ETL/ELT strategy and implementation to integrate historical and current data sources with a focus on scalability and performance.
• Implement and maintain data security controls, such as encryption, role-based access controls (RBAC) policies, privacy standards, and adherence to governance standards

Key Responsibilities

• Architect and develop a robust dimensional data model across OneStream, Hyperion, Oracle EBS, HCM, and Work brain systems.
• Design and optimize fact and dimension tables, data marts, and calculated metrics within the Azure Data Lake to support analytical and operational reporting.
• Lead ETL/ELT strategy and implementation to integrate historical and current data sources with a focus on scalability and performance.
• Implementing data quality rules, data lineage tracking, and proactive monitoring to ensure auditability, integrity and compliance.
• Develop and enforce data quality frameworks, including automated monitoring, validation rules, and reconciliation processes.
• Implement and maintain data security controls, such as encryption, role-based access controls (RBAC) policies, privacy standards, and adherence to governance standards
• Leading the development of metadata-driven processes and data marts that power self-service analytics and executive reporting.
• Driving high-performance data solutions that are future-ready for AI, machine learning, predictive analytics, and enable PowerBI analytical reports