Senior Data Modeling & Governance Consultant

Jobtailor; New York (NY); On-site; USD 150,000 - 200,000; Full time

Job summary

Jobtailor is seeking an experienced data architecture leader to create and implement enterprise-wide data models and to guide planning, development, and support for data models across the organization.

The role involves steering centers of excellence in process automation, new tool adoption, and data governance, while designing and maintaining the data warehouse and operational data stores. Strong emphasis on naming conventions, coding practices, and data validation is expected.

Qualifications

• Bachelor’s degree or equivalent experience in Technology, Business Management, Finance, Accounting, Marketing, Analytics or equivalent work experience.
• Ten or more years of relevant work experience required.
• Master’s Degree or equivalent experience preferred.
• Fifteen or more years of work experience preferred.
• Leading off shore and on shore experience with automation.
• Experience understanding processes.

Responsibilities

• Create and implement enterprise-wide data models.
• Lead Planning, Development, and Support functions for data models.
• Support multiple centers of excellence including process automation, new tool adoption, and data governance.
• Design, build & maintain the Data Warehouse and Operational Data Stores.
• Develop best practices for standard naming conventions and coding practices.
• Validate business data objects for accuracy and completeness.

Skills

data modeling

data warehouse

operational data stores

process automation

data governance

naming conventions

coding practices

business data validation

leadership

communication

organizational skills

Education

Bachelor's degree

Master's degree

Job description

Jobtailor is seeking an experienced data architecture leader to create and implement enterprise-wide data models and to guide planning, development, and support for data models across the organization.

The role involves steering centers of excellence in process automation, new tool adoption, and data governance, while designing and maintaining the data warehouse and operational data stores. Strong emphasis on naming conventions, coding practices, and data validation is expected.