Data Modeler

7 days ago

Summit, NJ, United States RIT Solutions, Inc. Full time
Job Title: Data Modeler
Location: Richmond, VA or Dallas, TX (Hybrid)
Duration: 6-month contract to hire with FTE potential

Overview: This group is migrating data from on-prem to cloud environments, has different data domains (i.e. sales, finance, marketing) and need to build comprehensive, enterprise data model to incorporate all that can be put into semantic reporting layer. Immediate goal is to build a few data models, starting with logical/conceptual and moving into physical, that can demonstrate value to business stakeholders. Room to scale the team to incorporate more Senior Modelers and BA resources.
  • Need experience in Erwin, DBT, or other tools to create logical and physical data models.
  • Define requirements with the business around reporting needs, building out data models around them, and tracing back data availability from their Oracle, Snowflake, and Databricks sources.
  • Apply dimensional and data vault modeling techniques.
  • Collaborate with data architects and solution architects to ensure best practices in data modeling. Existing Data Architect will be primary POC and support on this role.
  • Develop data models for data sources primarily in Oracle, transitioning to Snowflake and Databricks (majority curated data in Databricks).
  • Assist with create and maintenance of existing lineage documentation, tracking, source to target mapping, and data dictionaries.
  • Use Draw.io or Miro for conceptual data modeling--physical modeling tools still in discussion.
  • Implement snapshots and manage slowly changing dimensions Type 1, 2 mostly.
  • Ensure compliance with data governance practices, though immediate collaboration is not required.

Requirements:
  • Proficiency in data modeling using tools like Erwin, DBT, etc.
  • Strong understanding of data vault concepts and warehousing environments.
  • Familiarity with RDBMS, Snowflake, and Databricks or other warehousing
  • Experience with normalization and denormalization techniques.
  • Ability to create logical and physical data models and DDLs.
  • Knowledge of data lineage and data governance practices.
  • Experience with tools like Draw.io and Miro for logical data modeling preferred

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