Role Overview
As a Sr. Data Modeler, you will lead the creation and oversight of comprehensive data models that power enterprise analytics and operations. Your work will ensure data is structured for clarity, consistency, and compliance, serving both current needs and future scalability.
Key Responsibilities
- Develop and sustain conceptual, logical, and physical data models to support large-scale data platforms and analytics workflows.
- Evaluate and enhance existing data structures, databases, and pipelines to improve efficiency, accessibility, and long-term maintainability.
- Collaborate with business analysts, engineers, and technical leads to convert business requirements into precise, standardized data definitions.
- Contribute to enterprise data governance by defining data quality rules, managing metadata, and maintaining thorough documentation practices.
- Lead data migration strategies, guiding the transition from legacy systems to modern cloud-based platforms.
- Support security and compliance efforts by integrating access controls and aligning with standards such as GDPR or HIPAA.
Qualifications
Applicants should bring at least seven years of experience in data modeling, data architecture, or related enterprise data roles. Proficiency in SQL and hands-on experience with modeling tools like ERwin or Visio are essential. Experience with cloud platforms—such as AWS, Azure, or Google Cloud—is required, along with familiarity with traditional relational databases like Oracle or SQL Server.
Strong knowledge of data warehouse design, dimensional modeling techniques, and ETL/ELT pipelines is expected. Prior involvement in data governance, metadata management, and quality assurance initiatives is critical for success in this role.
Preferred candidates will have exposure to Big Data technologies and modern data processing frameworks, enhancing their ability to operate across evolving data landscapes.
Technical Environment
Tools and platforms include ERwin, Visio, AWS, Azure, Google Cloud, Oracle, SQL Server, and SQL. Experience across both cloud and on-premises environments is highly valued.
