US LBM Domain Data Architect
Summary
Domain Data Architect at US LBM (a national building-materials distributor) who owns the data architecture strategy and roadmap for a defined business domain, designing scalable governed data models, integration patterns, and analytics-ready solutions using Snowflake, MongoDB, PostgreSQL, Kafka, OpenFlow, Azure, Tableau, and Matillion.
US LBM is one of the leading and fastest growing distributors of specialty building materials in the United States, with a team of over 13,000 employees located throughout the country. Since our founding in 2009, we have acquired over 100 companies and have expanded to more than 450 locations serving 37 states. US LBM is a progressive organization that promotes a unique culture that focuses on the value of its customers and associates. Developing our people is critical to our strategy and fostering our culture of empowerment.
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A Brief Overview
The 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
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US LBM Holdings, LLC, is an equal-opportunity employer. We do not discriminate on the basis of race, color, religion, creed, national origin or ancestry, sex, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, marital status, military status, order of protection status, or any other legally recognized protected basis under federal, state, or local law.