Job Summary:
As a Senior Lead Data Modeler you will be responsible for designing, implementing, and maintaining sophisticated data models and information architecture frameworks that support business objectives, with a strong emphasis on data warehousing, semantic modeling, and dimensional modeling. This role requires a deep understanding of data architecture principles and the ability to translate complex business requirements into scalable and efficient data solutions. The Senior Data Modeler/Senior Information Architect will leverage the latest trends in data modeling, including data mesh, data fabric, and AI-driven modeling techniques, to optimize data processes and drive data-driven decision-making.
Key Responsibilities:
- Design and develop advanced data models and information architecture frameworks that meet business requirements and adhere to industry best practices, focusing on data warehousing, semantic modeling, and dimensional modeling techniques.
- Collaborate with business analysts, data engineers, and other stakeholders to gather and analyze data requirements.
- Create detailed modeling requirements and meta models to ensure comprehensive representation of business needs and data structures.
- Implement data modeling solutions using tools such as ERwin, PowerDesigner, or similar, with a focus on creating robust data warehouse architectures.
- Develop conceptual, logical, and physical data models to represent business requirements and data structures effectively.
- Integrate modern data modeling approaches such as data mesh and data fabric to enhance data accessibility and governance.
- Utilize AI-driven modeling techniques to automate and optimize data model creation and maintenance.
- Introduce, enhance, and govern data modeling practices within the software development lifecycle (SDLC) to ensure consistency, quality, and compliance in the data space.
- Ensure data models and information architecture frameworks are optimized for performance, scalability, and integration within the SDLC framework.
- Maintain and update existing data models and information architecture frameworks to accommodate changes in business needs and technology advancements.
Required qualification, capabilities and skills:
- Bachelor’s degree in Computer Science, Information Systems, or a related field; Master’s degree preferred.
- Minimum of 20 years of experience in data modeling, data architecture, or related roles.
- Extensive experience in Information Architecture, including data flow design, metadata management, and data lineage.
- Proven track record in developing and implementing comprehensive information architecture frameworks.
- Proficiency in data modeling tools, with significant experience in various ERwin versions and products, including ERwin Data Modeler, ERwin Data Intelligence, and ERwin Web Portal.
- Experience with multiple modeling tools such as DB Artisan, Embarcadero, and Hackolade data modeling tools.
- Strong understanding of relational and non-relational database systems, including NoSQL databases.
- Extensive experience with data warehousing, semantic modeling, and dimensional modeling.
- In-depth knowledge of AWS technologies and cloud-based data solutions, with a focus on delivering large-scale enterprise-class data platforms and data products.
- Familiarity with data mesh and data fabric concepts.
Preferred qualification, capabilities and skills:
- Experience in the financial services industry.
- Knowledge of big data technologies such as Hadoop, Spark, or similar.
- Experience with cloud-based databases such as Databricks, Snowflake, and Amazon Redshift.
- Certification in data modeling, data architecture, or AWS technologies.
- Experience in designing and implementing information architecture frameworks.
- Proven track record in establishing and maintaining data governance frameworks and processes.
- Proficiency with Jade products for data modeling and management.
- Experience with Integrated Customer Data Warehouse (ICDW) solutions.
- Expertise in Teradata for large-scale data warehousing and analytics.