Data Architect

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  Data Engineering — pipeline design, ingestion standards, storage architecture

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  Analytics Engineering — dbt modeling, semantic layer, data mart design

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  Data Science — feature stores, training data infrastructure, model serving data

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  Decision Science — reporting layer architecture, metric definitions, performance

• 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

• 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

• 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)

We offer competitive, meaningful benefits in every country where we operate. While they vary by location, here's 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

• Learning and development resources, including professional development tools and tuition reimbursement, 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.