A Brief OverviewThe US LBM Domain Data Architect translates enterprise data strategy into scalable, governed data solutions for a defined business domain, such as Customer, Product, Supply Chain, Finance, Operations, or Analytics. This person defines domain-level data models, integration patterns, analytics readiness, and data quality standards while partnering with engineering, integration, product, analytics, and platform teams.
What you will do- Own the data architecture strategy, roadmap, and standards for a defined business domain.
- Translate enterprise data principles into practical domain data models, patterns, ownership models, and governance practices.
- Define authoritative data entities, relationships, integration touchpoints, and consumption models for applications and analytics.
- Lead data architecture reviews for new initiatives, migrations, enhancements, and platform decisions.
- Ensure alignment with enterprise standards for modeling, naming, security, privacy, lineage, retention, and scalability.
- Partner with engineering, product, analytics, integration, and platform teams to deliver trusted, reusable data solutions.
- Define source-to-consume reference architectures and ingestion patterns, including batch, API, event-driven, and CDC-based replication into landing and curated datasets.
- Evaluate data platforms, integration tools, modeling approaches, and vendor solutions (including MDM, catalog, quality, and document/NoSQL stores where applicable).
- Working experience using MongoDB, Snowflake, OpenFlow, PostreSQL, Kafka and data as a service architecture.
- Experienced AI agentic programming design and engineering.
Required For All Jobs- Perform other duties as assigned.
- Comply with all policies and standards.
- Adhere to Company's commitment to workplace safety.
- Participate in and complete assigned trainings.
Education Qualifications- Bachelor's Degree in Computer Science, Information Systems, Data Management, Engineering, or related field required. Equivalent education, training, and experience may be considered.
- Master's Degree in a related discipline preferred.
Experience Qualifications- 5+ years of experience in data architecture, data engineering, software engineering, or a related technical role.
- Experience designing data solutions across operational, analytical, warehouse, lakehouse, and application environments.
- Experience developing conceptual, logical, and physical data models and applying enterprise data governance standards.
- Experience with ingestion and integration patterns, including batch, APIs, event-driven architecture, and CDC/log-based replication (schema drift, incremental loads, idempotent merges, replay/backfill).
- Experience partnering with technical and business stakeholders to deliver analytics-ready data structures and support migration and impact analysis.
Skills and Abilities- Strong knowledge of enterprise data architecture, data modeling, governance, quality, lineage, and master/reference data concepts.
- Working knowledge of cloud data platforms (Azure preferred), enterprise warehouses (e.g., Snowflake), BI tools (e.g., Tableau), ETL/ELT (e.g., Matillion), streaming/Kafka patterns, APIs, and PostgreSQL operational data stores.
- Understanding of CDC design patterns, operational vs. analytical separation, MongoDB document modeling, and AI-assisted approaches to data design and documentation.
- Ability to translate enterprise strategy into practical domain-level standards, reference architectures, and delivery guidance.
- Strong communication, collaboration, stakeholder engagement, influence without authority, and mentoring skills
