Data Architect

SiteOne Landscape Supply•Roswell, GA

23d

About The Position

Join our team as a Data Architect responsible for designing, governing, and evolving our enterprise data architecture to ensure consistent, scalable, and reliable data. Own and evolve enterprise data architecture across the custom point-of-sale database, data warehouse, and semantic models to support long-term business and analytics strategy. Assess current data structures and lead improvements to increase consistency, reuse, scalability, and clarity across the organization. Establish and govern data modeling practices, including standards, naming conventions, and recommended approaches. Select and maintain the data modeling and documentation tool used as the system of record. Provide architectural leadership for data initiatives by partnering on application and system design to ensure data structures align with enterprise architecture and scale over time. Review and approve data model and schema changes to protect integrity, reduce duplication, and ensure adherence to standards. Establish and enforce a formal data architecture review and change control process. Define and standardize data integration architecture and patterns to ensure data movement is scalable, efficient, and consistent, with clear systems of record and sources of truth. Lead data governance efforts by defining data definitions, ownership, lineage, and stewardship practices to promote trust, consistency, and transparency in data use. Partner with business and technology stakeholders to align data architecture with priorities and ensure data supports key decision-making. Shape and influence long-term data platform strategy by evaluating technologies, recommending improvements, and guiding evolution of the data ecosystem to support growth and advanced analytics.

Requirements

Bachelor's Degree
Minimum 5 years of relevant Data Architecture experience
Strong expertise in data modeling (dimensional modeling and relational design)
Deep understanding of data architecture across operational systems, data warehouses, and semantic models
Knowledge of data governance practices (lineage, stewardship, and metadata management)
Proficiency with SQL and experience working with enterprise data platforms
Familiarity with Microsoft data technologies (SQL Server, SSIS, SSAS, and Power BI)
Experience with data modeling and documentation tools
Strong analytical and problem-solving skills with a focus on scalability and performance
Experience working with semantic models and analytical layers
Excellent communication skills with the ability to work across technical and business teams
Ability to influence design decisions and guide development teams toward best practices
Experience evaluating and selecting data tools and technologies
Ability to design and evolve enterprise data architecture aligned with long-term business and technology strategy

Nice To Haves

Experience defining and implementing enterprise data standards and governance frameworks
Experience designing and optimizing data integration patterns and pipelines
Exposure to modern data platforms or cloud-based architectures
Experience working with semantic models and analytical layers

Responsibilities

Own and evolve enterprise data architecture across the custom point-of-sale database, data warehouse, and semantic models to support long-term business and analytics strategy
Assess current data structures and lead improvements to increase consistency, reuse, scalability, and clarity across the organization
Establish and govern data modeling practices, including standards, naming conventions, and recommended approaches
Select and maintain the data modeling and documentation tool used as the system of record
Provide architectural leadership for data initiatives by partnering on application and system design to ensure data structures align with enterprise architecture and scale over time
Review and approve data model and schema changes to protect integrity, reduce duplication, and ensure adherence to standards
Establish and enforce a formal data architecture review and change control process
Define and standardize data integration architecture and patterns to ensure data movement is scalable, efficient, and consistent, with clear systems of record and sources of truth
Lead data governance efforts by defining data definitions, ownership, lineage, and stewardship practices to promote trust, consistency, and transparency in data use
Partner with business and technology stakeholders to align data architecture with priorities and ensure data supports key decision-making
Shape and influence long-term data platform strategy by evaluating technologies, recommending improvements, and guiding evolution of the data ecosystem to support growth and advanced analytics