Data Modeler

1 Day ago • 12 Years +

Job Summary

Job Description

This Data Modeler role requires 12+ years of experience in Conceptual, Logical, and Physical Data Modeling. The role involves using Erwin Data Modeling Software, creating database objects, reviewing and tuning SQL scripting, and data analysis and database design. The candidate should have at least 1 year of experience in a cloud environment like AWS, Azure, or Google. The role also needs good knowledge of metadata management, data modeling and related tools. Experience with data warehouse design and development, datalake, and enterprise big data platforms is required. The candidate should have experience in data warehouse, datalake, and enterprise big data platforms in multi-data-center contexts required. Understanding of modeling strategies such as relational (logical, physical), star, snowflake, unstructured, to support OLTP, Warehousing and Data Marts, Data Lakes, MDM is needed. Excellent organization, analytical, and communication skills are also important.
Must have:
  • 12+ years of Data Modeling experience.
  • Hands-on experience with Erwin Data Modeling Software.
  • Experience creating database objects.
  • Experience with SQL scripting.
  • 1+ year of experience in cloud environment.
  • Experience in data analysis and database design.
  • Knowledge of database platforms (Oracle, Postgres, Hadoop, Snowflake, Netezza, DB2).
  • Experience in a data warehousing & Business intelligence
  • Good knowledge of metadata management and related tools.
  • Experience in data warehouse design and development.
  • Knowledge of modeling strategies (relational, star, snowflake, unstructured).
  • Excellent organization, analytical, and communication skills.

Job Details

 Requirements
  • 12+ years of experience in Conceptual, Logical and Physical Data Modeling experience.
  • Erwin Data Modeling Software hands-on experience
  • Create database objects.
  • Create, review and tune SQL scripting.
  • Must have 1+ year of experience in cloud environment (such as AWS, Azure or Google)
  • Data analysis and Database design experience.
  • Knowledge understanding of different database platforms, such as, Oracle, Postgres, Hadoop, Snowflake, Netezza, DB2.
  • Proven experience in a data warehousing & Business intelligence
  • Good knowledge of metadata management, data modeling, and related tools (Erwin, ER Studio, Oracle Designer or PowerDesigner)
  • Data Warehouse - Experience in data warehouse design and development, Experience with data warehouse, datalake, and enterprise big data platforms in multi-data-center contexts required.
  • Knowledge and in depth exposure to modeling strategies, such as relational (logical, physical), star, snowflake, unstructured, to support OLTP, Warehousing and Data Marts, Data Lakes, MDM).
  • Excellent organization, analytical, and communication skills.
Work Environment 
This job operates in a professional office environment. This role routinely uses standard office equipment, including but not limited to, computers, phones, and photocopiers.
 
Physical Demands 
This position requires the frequent and repetitive use of a computer, keyboard, and mouse. Hand and finger dexterity is required. 
 
Other Duties 
Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.
 
EEO 
Saama provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

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