openashbyhqleadershipforeducationalequity
Data Architect
Instructure
LocationMexico
WorkplaceRemote
EmploymentFullTime
Posted2026-06-11T02:47:40.975+00:00
Last observed2026-06-13 05:24:16.382400
Job idleadershipforeducationalequity-instructure:ashbyhq:08e0b60f-0fd2-435c-9d26-2a1c034c1c35
At Instructure, we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers. We do this by giving smart, creative, passionate people opportunities to create awesome. And that's where you come in: We are looking for a Data Architect to join our Business Data & Insights organization. This is a senior, highly cross-functional role responsible for defining, governing, and evolving the enterprise data architecture that powers our Data Engineering, Analytics Engineering, Data Science, and Decision Science teams—while maintaining a close strategic partnership with our Product Data organization. You will serve as the connective tissue between how data is produced and how it is consumed—ensuring that our data assets are reliable, well-modeled, semantically consistent, and designed to scale. This role sits within the Business Data & Insights organization, bringing both technical authority and a deep understanding of business context. While you will work in close partnership with the Product Data team—collaborating on shared standards, platforms, and data contracts—you are organizationally independent from both Product and Engineering, giving you the perspective and authority to advocate for enterprise-wide data integrity. WHAT YOU WILL DO - 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 - Mentor and guide engineers and analytics engineers on architectural patterns and data modeling best practices WHO YOU'LL WORK WITH Within Business Data & Insights: - Data Engineering — pipeline design, ingestion standards, storage architecture - Analytics Engineering — dbt modeling, semantic layer, data mart design - Data Science — feature stores, training data infrastructure, model serving data - Decision Science — reporting layer architecture, metric definitions, performance Cross-functional Partnership: - Product Data Team — shared standards, data contracts, source alignment - Product and Engineering Executives — architectural roadmap, governance, strategic investment - Engineering / Platform teams — infrastructure alignment and platform APIs - Legal & Compliance — data privacy, retention, and classification architecture WHAT YOU'LL NEED TO KNOW/HAVE: - 8+ 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 model
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