Data Modeling Professional

1. Data Modeling Development: - Design, create, and maintain logical and physical data models that align with business requirements, using ERwin and other modeling tools. - Develop and implement dimensional models to support analytical and reporting needs, ensuring data integrity and consistency. 2. ETL Process Design: - Collaborate with ETL developers to define and optimize data extraction, transformation, and loading processes, ensuring timely and accurate data delivery. - Identify and address any ETL-related issues or inefficiencies, and work on improving overall data pipeline performance. 3. SQL Query Development: - Write, optimize, and maintain complex SQL queries for data analysis and modeling purposes, providing insights to stakeholders and decision-makers. - Conduct data validation and reconciliation activities to ensure data quality and correctness. 4. Collaboration and Communication: - Work closely with cross-functional teams, including data analysts, business intelligence developers, and stakeholders, to understand data needs and provide appropriate modeling solutions. - Communicate modeling concepts and methodologies effectively to non-technical stakeholders. 5. Documentation and Standards: - Document data models, ETL processes, and best practices to ensure knowledge sharing within the team and compliance with company standards. - Participate in the establishment and maintenance of data governance and modeling standards. 6. Performance Monitoring and Optimization: - Monitor the performance of existing data models and ETL processes, implementing improvements as necessary to optimize performance and scalability. - Evaluate emerging tools and technologies that can enhance modeling processes and overall data management capabilities. 7. Training and Mentoring: - Provide training and mentorship to junior data team members on data modeling techniques and best practices. - Lead workshops and knowledge-sharing sessions to enhance team expertise in data modeling and ETL processes. 8. Adherence to Best Practices: - Stay updated on industry trends and best practices related to data modeling and ETL processes, applying insights to improve data workflows at Trask. - Ensure compliance with data privacy regulations and company policies throughout all data modeling activities.