US LBM Domain Data Architect

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