Senior Data Architect

🔥 14 hours ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Goods & Services

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2013

🤖 Artificial Intelligence

🏢 Enterprise

🤝 B2B

Artificial Intelligence • Enterprise • B2B

Goods & Services is a product design and digital engineering company that helps enterprises design, build, and scale AI-powered products, platforms, and customer experiences. They provide services across Data & Artificial Intelligence, Experience Strategy & Design, and Technology & Engineering (cloud, software, hardware), focusing on modernizing data infrastructure, building digital product ecosystems and global web systems, and delivering enterprise-grade cloud and platform engineering for market-leading B2B clients.

📋 Description

• Define and own the enterprise data architecture strategy, including conceptual, logical, and physical data models across the organization's core domains • Establish and govern data standards, naming conventions, schema design principles, and modeling best practices used by Data Engineering and Analytics Engineering teams • Lead the design of scalable, reusable data products in the semantic and analytical layers, ensuring consistency across Decision Science, Data Science, and self-service consumption • Partner with the Product Data team to align on shared architectural standards, data contracts, and platform decisions—acting as a peer and collaborator, not a dependency • Evaluate and advise on data platform and tooling decisions (cloud data warehouses, lakehouse patterns, orchestration, metadata management, cataloging) • Identify and resolve architectural gaps, redundancy, and data quality risks across the data estate • Contribute to—and in many cases lead—the development of a business glossary, data catalog, and enterprise ontology for key data domains • Act as a senior advisor to Data Science on data availability, feature engineering infrastructure, and model data requirements • Collaborate with Decision Science leadership to ensure analytical data models are structured for performance, clarity, and governed self-service • Champion data governance, lineage, and observability as first-class architectural concerns

🎯 Requirements

• 5+ years of experience in data architecture, data engineering, or a closely related discipline in a complex, multi-team data environment • Demonstrated experience designing and governing enterprise data models across transactional, analytical, and semantic layers • Deep expertise in modern data stack patterns: cloud data warehouses (Snowflake, BigQuery, Databricks), lakehouse architectures, dbt, data cataloging tools • Strong command of data modeling methodologies—dimensional modeling, Data Vault, OBT, and when to apply each • Experience establishing or evolving data governance programs including metadata management, lineage, and data quality frameworks • Ability to work across technical and business stakeholders—translating architectural decisions into clear business value • Experience partnering with Data Science teams on feature engineering, training datasets, or MLOps data infrastructure • Excellent communication and documentation skills; you write clearly about architecture for both technical and executive audiences • Experience working in matrix or cross-functional environments, navigating organizational boundaries without direct authority

🏖️ Benefits

• Professional development opportunities