Data Modeler

QUESTIONS:

Smucker does not interview candidates directly. Please ask the candidates the following questions and provide feedback on their answers to the Hiring Manager.

Question 1: Tell me about a time when you had to completely redesign a data model that was already in production. What drove that decision and what was your approach?

Question 2: Give me an example of when you discovered a major data quality issue that traced back to a modeling decision. How did you identify and resolve it?

Question 3: You're designing a fact table for sales transactions. Walk me through how you would determine the grain and which slowly changing dimension strategy you would use for the product dimension. Why?

DETAILED REQUIREMENTS:

• Dimensional Modeling (Kimball Methodology):
  
• Apply Kimball methodology to translate business requirements into dimensional models, focusing on user-friendly, business-driven views of data in ER Studio.
  
• Design and maintain star schemas, ensuring optimal query performance and ease of use for analytics and Data Science.
  
• Identify and define fact tables, dimension tables, surrogate keys, and conformed dimensions for cross-functional analysis.
  
• Data Model Design & Documentation:
  
• Develop conceptual, logical, and physical data models using ER Studio.
  
• Reverse engineer existing databases and create entity-relationship diagrams (ERDs) to document data structures and relationships.
  
• Maintain metadata, data dictionaries, and business process flow documents for all models
  
• Translate business requirements and data constraints into robust dimensional models that supporting actionable insights and business friendly scalable analytics
  
• Collaboration & Stakeholder Engagement:
  
• Work closely with business analysts, data owners, data producers, data engineers, data governance analysts and subject matter experts to fully understand objectives, decision making processes, gathering requirements and validating models.
  
• Engage with technical experts to assess the realities of source system data via high-level profiling and data validation for feasibility and integrity
  
• Participate in sprint planning, backlog reviews, and hand-offs with data engineering and governance teams.
  
• Collaborate with other data modelers to create consistency in conformed dimensions across all analytics data.
  
• Data Quality & Governance:
  
• Ensure models adhere to data governance, security, and compliance standards.
  
• Validate data flows, enforce best practices, and review new requirements and changes to data pipelines.
  
• Support data quality initiatives and audit table requirements.
  
• Tool & Platform Expertise:
  
• Use ER Studio for model creation, documentation, and version control.
  
• Reimagine current state models on platforms such as Oracle, SQL Server, Informatica, Spotfire and Tibco TDV as needed.
  

REQUIRED SKILLS: (Please BOLD top 3 required skills)

• Bachelor's degree in computer science, Information Systems, or related field.
  
• 7+ years of experience in data modeling for analytics or data warehousing with strong expertise in Kimball methodology, dimensional modeling, and star schema design.
  
• Proficiency with ER Studio or similar data modeling tools.
  
• 3+ years? of? Data Engineering? experience with relational databases (Oracle?Exadata, SQL Server,?Informatica, Tibco Data Virtualization, Databricks?or similar tools).?
  
• Solid understanding of data governance, metadata management, and data quality principles.
  
• Excellent communication and collaboration skills.
  

NICE TO HAVE SKILLS:

• Experience with agile methodologies and sprint-based project delivery.
  
• Familiarity with business intelligence platforms and reporting tools.
  
• Ability to translate complex business requirements into scalable data models.
  
• Knowledge of data integration, ETL/ELT pipelines, and master data management.
  

DESCRIBE A DAY IN THE LIFE OF THIS ROLE: The Data Modeler will design, develop, and maintain data models that support analytics and business intelligence initiatives. This role leverages the Kimball methodology for dimensional modeling, implements a star schema architecture, and utilizes ER Studio for data modeling and documentation. The Data Modeler collaborates with business stakeholders, data engineers, and analytics teams to ensure data structures are optimized for reporting, data science, integration, and scalability. Solves unique and complex Data Modeling problems impacting a domain, with a keen understanding of touchpoints with adjacent areas and relationships to business process.

PROJECT STATEMENT: Cloud Analytics Platform Implementation or CAPI is a large Program made of 6 project teams focused on delivering new data warehouse, analytics and visualization platforms for the company. This project is standing up several new applications and modernizing our current state processes. This person would assist in the completion of rationalizing and building of new data models for the many areas of the business. It?s a PMO led project and is following a Hybrid Iterative Waterfall Methodology.

BUSINESS OBJECTIVE: Modernizing our Data and Analytics tools with cloud-based solutions to accelerate decision making. Governing our data to provide standardization across the business to increase confidence in the data provided. Creating insights through visualization and storytelling in reporting to uncover predictions leading to opportunities.

DETAILED REQUIREMENTS: