Posted:5 days ago|
Platform:
On-site
Full Time
Develop conceptual, logical, and physical data models to support core business processes across domains.
Translate complex business workflows into structured data architectures supporting both transactional (OLTP) and analytical (OLAP) environments.
Ensure models are flexible, scalable, and aligned with evolving operational and analytical needs.
Define and enforce data modeling standards, best practices, and governance principles.
Partner with business stakeholders, analysts, architects, and operational teams to capture and interpret data requirements.
Build empathy-driven models that reflect real-world business needs and challenges.
Present model designs and facilitate review sessions with both technical and business stakeholders.
Mentor junior data modelers and data analysts, providing technical guidance and knowledge sharing.
Ensure data models adhere to organizational governance policies and industry regulations (e.g., data privacy, security, retention).
Collaborate with compliance, security, and audit teams to embed necessary controls into the data architecture.
Use industry-standard data modeling tools (e.g., Erwin, Power Designer, ER/Studio, or equivalent).
Design models optimized for both high-volume transaction systems and complex analytical/reporting needs.
Collaborate with ETL developers, data engineers, and database administrators to ensure seamless integration, performance optimization, and scalability.
Stay up to date with emerging trends and technologies in data modeling, data platforms, and analytics.
Identify opportunities for process improvements and automation within data workflows.
Support continuous improvement initiatives to streamline data operations and enhance reporting efficiency.
Bachelor's degree in Information Systems, Computer Science, Data Management, or related field, or equivalent experience.
Extensive experience in data modeling and data architecture across varied domains.
Proven ability to work closely with diverse stakeholder groups to capture detailed requirements and translate them into actionable models.
Strong expertise in designing and managing conceptual, logical, and physical data models.
Hands-on experience with relational, dimensional, and NoSQL data platforms.
Expertise in data modeling principles and methods across multiple modeling paradigms.
Experience with enterprise-scale platforms (data warehouses, data lakes, big data ecosystems).
Proficiency in data modeling tools (Erwin, PowerDesigner, ER/Studio, or others).
Strong communication skills to bridge technical and business teams.
Knowledge of data privacy, compliance, and governance requirements (e.g., GDPR, CCPA, or equivalent frameworks).
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