Enterprise Data Modeler / Data Architect

Steris Corporation•Mentor, OH

2d•Hybrid

About The Position

The Enterprise Data Modeler / Data Architect designs and leads enterprise-scale data models that power cloud data warehouses, data lakes, and analytics platforms. This role partners closely with business stakeholders, data engineers, and analytics teams to translate business and analytical needs into scalable, high‑quality data models and metadata that enable trusted, self-service reporting, advanced analytics, and data science use cases.

Requirements

Bachelor’s degree in Computer Science, MIS, Informatics, or related field
10+ years of experience in enterprise data modeling, preferably in cloud-based data warehouse and data lake environments.
Strong expertise in dimensional modeling (star and snowflake schemas) and relational data design.
Hands-on experience with cloud data platforms such as Snowflake, AWS Redshift, or Google BigQuery.
Advanced SQL skills and experience designing database schemas and structures.
Proven experience with Enterprise Data Catalogs and Business Glossaries, including tools like Collibra, Alation or MS Purview
Experience with defining metadata standards, mandatory attributes, and data stewardship workflows.
Ability to collaborate on metadata strategy supporting self-service BI, analytics, and data governance.
Proficiency with data modeling tools (e.g., Erwin, ER Studio, IBM InfoSphere Data Architect or similar).
Solid understanding of data engineering concepts, ETL/data pipelines, data lineage, and integration practices.
Experience embedding metadata, naming standards, and data quality practices into data platforms and development processes.
Excellent communication and collaboration skills across business, analytics, and technology teams.

Nice To Haves

Expertise with data and metadata modeling best practices to design data repositories optimized to support AI/ML applications and use cases is highly desired.

Responsibilities

Design, implement, and maintain conceptual, logical, and physical data models for enterprise data warehouses, data lakes, and specialized data stores.
Collaborate with business and technical stakeholders to gather requirements and translate them into efficient, scalable data designs.
Define and govern enterprise data modeling and metadata standards, best practices, and design patterns.
Partner with data engineering teams to ensure data models align with ETL/data pipelines, lineage, and performance requirements.
Develop and maintain data documentation, including data dictionaries, business glossary entries, and data catalog metadata.
Support and evolve the Enterprise Data Catalog and Business Glossary, capturing business, technical, and operational metadata.
Work with Data Owners and Data Stewards to ensure key data elements have clear definitions, ownership, lineage, and data quality context.
Serve as a technical leader and mentor, promoting data modeling, metadata, and governance best practices across the organization.