Data Modeler

Job Summary:

As a Data Modeler, you will be collaborating closely with Analysts, Engineers, and Architects to design data models that reduce data redundancy, streamline data movement, and improve information management. The Data Modeler will work closely with business counterparts to develop technical requirements and specifications for data analytics projects. This role will have overall oversight over creation of conceptual, physical, logical, analytical data models and associated data maps/documents. The data modeler must have excellent technical and people skills, and knowledge of programming languages to build/manage data models.

We are a small team of highly skilled and motivated professionals who are passionate about data and analytics. It is a highly entrepreneurial environment where you will be empowered to act on your ideas. We offer flexibility on work from home/office based on your personal needs.

Qualifications:

Bachelor's degree in a relevant discipline (e.g., computer science), or equivalent work experience.

Experience with physical and relational data modeling.

Knowledge of data modeling best practices and data modeling tools.

Knowledge of mathematical and statistical analysis.

Knowledge of RDBMS platforms.

Data language skills (Python, T-SQL, etc.).

Strong people skills.

Willingness to learn the business needs.

Responsibilities:

Analyze and translate business needs into data models

Aid end-users in understanding established data models.

Work with the development team to create conceptual data models and data flows.

Validate, publish, and maintain conceptual, logical, and physical data models.

Evaluate cloud data systems for variances, discrepancies, and efficiency.

Troubleshoot and optimize data systems.

Support the needs of end consumers (e.g. dashboard design, data summaries, facilitating implementation of business strategies and missions)

Define and govern data modeling and design standards, tools, best practices, and related development methodologies for the organization.

Additional Success Factors:

Knowledge and experience with the Azure environment are a plus.

The ability to communicate complex ideas in a simple manner.

Open to all US locations