Principal Practice Enterprise Architect Data at Sherwin-Williams, Cleveland, OH

Principal Practice Enterprise Architect Data at Sherwin-Williams in Cleveland, OH. Est. up to $160k. Apply with swipeandhired.

The Principal Practice Enterprise Architect, Data is the architecture decision maker for data across the enterprise. The role owns the standards, reference architecture, technology selections and roadmap for how data is stored, modeled, moved, governed and served, and every portfolio conforms to them. When this role sets the enterprise standard for the data platform, a modeling approach or a data product pattern, that is the standard: Portfolio Architects design within it, Solution & Domain Architects conform to it and platform teams implement it. It works with data, analytics, security and privacy leaders as a peer.

• Own enterprise standards, patterns and reference architectures for data: the enterprise data platform and lakehouse, data modeling, master and reference data, analytics and reporting, and how AI workloads draw on the data foundation
• Own data technology and platform selection for the enterprise: data platform, storage and processing, master data management, analytics and BI, catalog and data quality tooling, in consultation with the Integration & DevOps, AI and Infrastructure Practice Architects
• Own data architecture guardrails with Security, Privacy and Data Governance: classification, retention, access patterns and the conditions under which data may be shared or leave the platform
• Maintain the enterprise data platform roadmap: capability expansion, version currency and sunset planning, as architecture input to investment decisions
• Review solution designs for conformance to data standards, and advise Portfolio Architects where their decisions intersect data without overriding them
• Keep Enterprise Data & Insights platform delivery aligned to the enterprise standard, and provide the data foundation the Enterprise AI Game Changers initiatives build on
• Run the data technology radar: assess what is emerging, maturing or declining in data platforms, modeling and analytics
• Build data architecture capability across the architect population: patterns, enablement and hands-on guidance for Solution & Domain Architects
• Serve as a standing member of architecture governance, contributing data intelligence to enterprise strategy and investment decisions

This is a remote position.
This position is not eligible for sponsorship for work authorization now or in the future, including conversion to H1-B visa.
Job duties include contact with other employees and access confidential and proprietary information and/or other items of value, and such access may be supervised or unsupervised. The Company therefore has determined that a review of criminal history is necessary to protect the business and its operations and reputation and is necessary to protect the safety of the Company’s staff, employees, and business relationships.
Must be eighteen years or older

Minimum Qualifications:

• Must be at least 18 years of age
• Must be legally authorized to work in the country of employment without now or in the future requiring sponsorship for employment visa status (e.g., OPT, CPT, H1B, EB-1, etc.)
• Bachelor's degree in Computer Science or Information Technology, or in lieu of a degree, at least 18 years of experience in technology delivery
• 15+ years in technology, including 5+ years of hands-on data engineering or software engineering and 5+ years in architecture or deep technical leadership roles
• Production experience designing and governing enterprise data platforms at scale on Databricks: lakehouse and medallion architecture, Delta Lake, Unity Catalog governance, data modeling, master data management, analytics and data products. Advisory-only data experience does not qualify
• 3+ years setting enterprise technology standards and making platform selection decisions across multiple business units or delivery teams
• Working depth in integration patterns and the AI and ML data lifecycle, enough to design a data foundation that AI and analytics workloads reuse rather than duplicate
• Current hands-on use of Databricks (notebooks, SQL, workflows, Unity Catalog) and AI code assist tooling; evaluates platforms directly rather than through vendor material
• Track record of influencing senior technical leaders as a peer and enforcing standards across delivery teams without creating bottlenecks

Preferred Qualifications:

• TOGAF Level 2, CISSP, CEAP, CSA, CSEA

Travel: 10-15%