Domain Data Architect
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Job Description
Domain Data Architect designing governed data models, integrations, and analytics solutions. Supporting US LBM, a leading U.S. specialty building-materials distributor.
Responsibilities:
- 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
- Perform other duties as assigned
- Comply with all policies and standards
- Adhere to the Company's commitment to workplace safety
- Participate in and complete assigned trainings
Requirements:
- Bachelor's Degree in Computer Science, Information Systems, Data Management, Engineering, or related field required; equivalent education, training, and experience may be considered
- 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
- 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
- Working experience using MongoDB, Snowflake, OpenFlow, PostgreSQL, Kafka, and data as a service architecture
- Experienced AI agentic programming design and engineering
- Strong communication, collaboration, stakeholder engagement, influence without authority, and mentoring skills
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