Data Architect

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 thats where you come in.

Job Title
Data Architect

Location
Remote

Department
Business Data & Insights

Level
Senior Technical Leader

Shape How Data Flows Across the Enterprise
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, 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 organizations 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

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 Youll 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 Youll 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 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

It Would Be a Bonus If You Also Had

Experience in a company with both a centralized data function and an embedded Product Data or Data Platform team

Familiarity with semantic layer tools (Cube, MetricFlow, LookML) and headless BI patterns

Background in data mesh, data product, or federated data governance operating models

Exposure to real‑time or streaming data architecture (Kafka, Flink, Spark Streaming)

Experience with data privacy‑by‑design architecture and regulatory frameworks (GDPR, CCPA)

What Sets You Apart

You think in systems: You design for the entire data lifecycle—not just the next sprint—and can articulate the long‑term tradeoffs of every architectural choice.

You lead through influence: You dont need a reporting line to drive alignment. You build credibility through expertise, communication, and a clear point of view.

Youre a bridge‑builder: You thrive operating between teams—Business and Product Data, engineering and the business—and know how to find the win‑win.

You balance vision and pragmatism: You have strong architectural opinions but know how to phase delivery, make tradeoffs, and ship real value while keeping the north star in view.

Get on all the awesome at Instructure!
We offer competitive, meaningful benefits in every country where we operate. While they vary by location, heres a general idea of what you can expect:

Competitive compensation, plus all full‑time employees participate in our ownership program - because everyone should have a stake in our success.

Flexible work culture. Our remote, hybrid and in‑office collaboration spaces vary by role, team and location.

Generous time off, including local holidays and our annual “Dim the Lights” period in late December, when teams are encouraged to step back and recharge based on departmental needs.

Comprehensive wellness programs and mental health support

Annual learning and development stipends to support your growth

The technology and tools you need to do your best work

Motivosity employee recognition program

A culture rooted in inclusivity, support, and meaningful connection

We believe in hiring great people and treating them right. The more diverse we are, the better our ideas and outcomes.

Instructure is an Equal Opportunity Employer. We comply with applicable employment and anti‑discrimination laws in every country where we operate.

All employees must pass a background check as part of the hiring process. To help protect our teams and systems, we’ve implemented identity verification measures. Candidates may be asked to verify their legal name, current physical location, and provide a valid contact number and residential address, in accordance with local data privacy laws.

Any attempt to misrepresent personal or professional information will result in disqualification.

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