Georgia Pacific
Lead Data Architect – Georgia Pacific
As a Lead Data Architect, you will be a key individual contributor responsible for shaping the future of our enterprise data landscape. Within the Data Management organization, you will provide hands‑on data architecture support for high‑value initiatives, ensuring our data assets are designed, structured, and governed for long‑term scalability, quality, and usability. You will work closely with Data Governance, Data Quality, the Data Platform team, and solution architects to define and deliver data models that align with enterprise standards while meeting business needs.
Responsibilities
Develop and own logical and physical data models across key domains, ensuring consistency, scalability, and alignment with enterprise standards.
Translate business requirements into conceptual, logical, and physical data structures.
Guide delivery teams on best practices for data modeling, schema design, and data lineage.
Review and refactor existing models where needed to optimize performance, clarity, and alignment with future‑state patterns.
Act as the dedicated Data Architect for priority enterprise initiatives—those representing significant investment, complexity, or cross‑domain impact.
Provide architectural oversight from discovery through deployment, ensuring data design decisions reduce long‑term technical debt and support enterprise data reuse.
Collaborate with data engineers, analytics developers, BI teams, and product owners to ensure implementation aligns with intended architecture.
Create clear handoffs, reusable patterns, and model documentation to streamline delivery execution.
Serve as a subject‑matter expert for modeling tools, naming conventions, structures, and data best practices.
Work closely with the Data Governance team to evolve standards for data products, metadata, documentation, and modeling conventions.
Help mature enterprise frameworks for data domain design, canonical models, and conformed dimensions.
Drive reuse by identifying patterns, shared entities, and opportunities for consolidation.
Partner with solution architects to ensure consistency between integration and data architecture.
Collaborate with the Data Platform team to ensure models are optimized for target technologies and support performance, security, and quality.
Ensure models reflect data quality rules and support the AI‑driven DQ tooling strategy.
Provide metadata that feeds Alation and supports transparency and trust in enterprise data assets.
Qualifications
Experience in data architecture, data modeling, or enterprise data design roles.
Experience building logical and physical data models for relational and/or cloud‑native platforms.
Understanding of dimensional modeling, 3NF, and hybrid patterns.
Hands‑on experience supporting large‑scale data engineering or analytics initiatives.
Ability to translate business needs into structured data designs.
Proven ability to simplify complex topics for technical and non‑technical audiences.
Experience in cloud‑based data platforms (Azure, AWS, or GCP), data lakes, and data lakehouses.
Experience working with metadata management or data intelligence tools (e.g., Alation).
Familiarity with enterprise data governance, data product concepts, and data quality frameworks.
Exposure to Denodo or similar data virtualization technologies.
Experience in a federated or hybrid data architecture model.
Experience in Agile environments or working with cross‑functional teams in iterative, fast‑paced delivery cycles.
Proactive communicator who can effectively convey complex technical concepts to non‑technical stakeholders.
Detail‑oriented, collaborative, and a continuous learner committed to staying up‑to‑date with industry trends and best practices.
Additional Information Equal Opportunity Employer, including disability and protected veteran status. The employer uses E‑Verify. Eligibility may depend on state law.
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Responsibilities
Develop and own logical and physical data models across key domains, ensuring consistency, scalability, and alignment with enterprise standards.
Translate business requirements into conceptual, logical, and physical data structures.
Guide delivery teams on best practices for data modeling, schema design, and data lineage.
Review and refactor existing models where needed to optimize performance, clarity, and alignment with future‑state patterns.
Act as the dedicated Data Architect for priority enterprise initiatives—those representing significant investment, complexity, or cross‑domain impact.
Provide architectural oversight from discovery through deployment, ensuring data design decisions reduce long‑term technical debt and support enterprise data reuse.
Collaborate with data engineers, analytics developers, BI teams, and product owners to ensure implementation aligns with intended architecture.
Create clear handoffs, reusable patterns, and model documentation to streamline delivery execution.
Serve as a subject‑matter expert for modeling tools, naming conventions, structures, and data best practices.
Work closely with the Data Governance team to evolve standards for data products, metadata, documentation, and modeling conventions.
Help mature enterprise frameworks for data domain design, canonical models, and conformed dimensions.
Drive reuse by identifying patterns, shared entities, and opportunities for consolidation.
Partner with solution architects to ensure consistency between integration and data architecture.
Collaborate with the Data Platform team to ensure models are optimized for target technologies and support performance, security, and quality.
Ensure models reflect data quality rules and support the AI‑driven DQ tooling strategy.
Provide metadata that feeds Alation and supports transparency and trust in enterprise data assets.
Qualifications
Experience in data architecture, data modeling, or enterprise data design roles.
Experience building logical and physical data models for relational and/or cloud‑native platforms.
Understanding of dimensional modeling, 3NF, and hybrid patterns.
Hands‑on experience supporting large‑scale data engineering or analytics initiatives.
Ability to translate business needs into structured data designs.
Proven ability to simplify complex topics for technical and non‑technical audiences.
Experience in cloud‑based data platforms (Azure, AWS, or GCP), data lakes, and data lakehouses.
Experience working with metadata management or data intelligence tools (e.g., Alation).
Familiarity with enterprise data governance, data product concepts, and data quality frameworks.
Exposure to Denodo or similar data virtualization technologies.
Experience in a federated or hybrid data architecture model.
Experience in Agile environments or working with cross‑functional teams in iterative, fast‑paced delivery cycles.
Proactive communicator who can effectively convey complex technical concepts to non‑technical stakeholders.
Detail‑oriented, collaborative, and a continuous learner committed to staying up‑to‑date with industry trends and best practices.
Additional Information Equal Opportunity Employer, including disability and protected veteran status. The employer uses E‑Verify. Eligibility may depend on state law.
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