OVERALL DESCRIPTION

The Senior Data Modeler is responsible for designing and implementing a robust and scalable data architecture. The role will work closely with business users, business analysts, product teams, development teams, and other data professionals to define and execute a comprehensive data architecture. The data modeler will identify the current data management challenges and address data modeling, data quality and data integrity issues. The ideal candidate will have a strong understanding of data modeling best practices, metadata management and data governance. The role works with Data Governance team to ensure compliance with policies, security standards, and regulatory requirements. Also works with AI/ML engineering team to capture features and data sets required for predictive models, AI/ML use cases.

SPECIFIC RESPONSIBILITIES

1. Collaborates with business users, business analysts, product teams, data and analytics engineers and others to understand data requirements and translate them into effective and efficient data models.
2. Develops conceptual, logical, and physical data models, ensuring alignment with best practices and data governance standards.
3. Optimizes data models for performance, scalability, and ease of use reporting.
4. Defines and adheres to the best practices for data modeling and naming conventions.
5. Conducts gap analysis of the current data landscape and identify areas for improvement.
6. Contributes to the development and maintenance of data dictionaries and metadata repositories.
7. Participates in data mapping and data lineage activities to ensure data integrity and traceability during the data migration process.
8. Identifies and resolves data modeling issues and provide recommendations for improvements.
9. Contributes to the creation of semantic layer that enables self-service analytics.
10. Facilitates data model review sessions with data and analytics engineering teams and others to assess and validate the proposed data model meets the business requirements.
11. Facilitates collaborative analysis and design sessions by leveraging strong written and verbal communication skills to ensure clear understanding and alignment among stakeholders.
12. Performs other duties as assigned.

QUALIFICATIONS AND EXPERIENCE

• Bachelor's degree in Computer Science, Information Technology or related field required.
• 10+ years of experience in architecting and building enterprise data models for both operational and analytical systems required.
• 5+ years of experience in data modeling tools like Erwin, ER Studio. Experience with multi-user modeling tool is preferred.
• 3+ years of data architecture experience in cloud data platforms (AWS, Azure) required.
• Expertise in conceptual, logical, physical data modeling and normalization, de-normalization techniques required.
• Established data architectures for relational and non-relational databases as well as dimensional modeling for data analytics required.
• Experience in integrating data models with BI tools and Data Catalogs preferred.
• Hands on experience with cloud data platforms like Snowflake, Databricks, AWS Redshift, Azure Synapse required.
• Strong proficiency in SQL, including writing complex queries for data analysis, data profiling, data validation and reconciliation required.
• Ability to analyze the structure and reverse engineer data models from various data formats like XML, JSON, AVRO, etc., required.
• Familiar with ETL/ELT tools and BI tools required.
• Understanding of data privacy regulations (e.g., GDPR, CCPA) and best practices for data security required.
• Experience working with Agile/Scrum methodologies required.
• Ability to communicate complex data architecture concepts and practices to both technical and non-technical stakeholders required.
• Excellent problem-solving skills, with a proactive and solution-oriented approach required.
• Stay abreast of the latest techniques and technologies relevant data modeling and cloud-based data platform required.