- Company Name
- Weyerhaeuser
- Job Title
- Senior Director of Data Management
- Job Description
-
Job Title: Senior Director of Data Management
Role Summary:
Lead enterprise‑wide data strategy, governance, and product development to empower AI, digital transformation, and operational excellence. Own data architecture, quality, security, and compliance across structured and unstructured sources, ensuring data assets are trusted, reusable, and customer‑driven.
Expactations:
- Deliver measurable value through data‑driven decisions, AI enablement, and process optimization.
- Scalable data product operating model with clear SLAs and service levels.
- Unified data ecosystem integrating finance, supply‑chain, industrial, geospatial, and unstructured data.
- Continuous improvement of data maturity, governance, and AI readiness.
Key Responsibilities:
- Define and execute enterprise data management strategy aligned with business goals and AI initiatives.
- Build, govern, and govern data products across silviculture, forecasting, pricing, manufacturing, real‑estate, energy, and geospatial domains.
- Embed governance framework and metrics‑driven culture for quality, adoption, efficiency, and ROI.
- Integrate SAP (S/4, C4C, BTP, BCP), MES/IIoT, ESGI, and other platforms into a unified data architecture.
- Govern industrial operations data and geospatial data for predictive maintenance, sustainability reporting, and digital twins.
- Lead enterprise data engineering for AI acceleration, feature store governance, semantic modeling, and conversational analytics readiness.
- Ensure compliance with privacy, sustainability, and regulatory requirements; implement data security protocols.
- Evaluate and implement modern data stack tools (Snowflake, dbt, Purview, ESRI, etc.) and emerging observability technologies.
- Collaborate with business, IT, AI, and vendor partners to align data strategy with enterprise objectives.
Required Skills:
- Strong leadership and team management in a matrixed environment.
- Deep expertise in enterprise data governance, data quality, metadata management, and data product lifecycle.
- Proven experience integrating SAP, MES/IIoT, geospatial, and unstructured data into a unified platform.
- Knowledge of AI/ML Data Engineering concepts, feature stores, semantic models, and conversational analytics.
- Familiarity with modern data stack (Snowflake, dbt, Purview, ESRI, etc.) and emerging data observability tools.
- Ability to translate business outcomes into data product requirements and deliver SLAs.
- Excellent communication, stakeholder management, and cross‑functional collaboration skills.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Information Systems, Data Science, Business Analytics, or related field.
- Master’s degree preferred.
- Certifications in data governance (CDMP, CSGMP), SAP data management, or AI/ML platform expertise (e.g., Microsoft Data Analyst, Tableau, Snowflake) welcome.