Data Architect

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‑modelled, 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 organisationally 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 organisation’s core domains
• Establish and govern data standards, naming conventions, schema design principles, and modelling 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, cataloguing)
• 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 modelling best practices

Who You'll Work With

Within Business Data & Insights:

• Data Engineering — pipeline design, ingestion standards, storage architecture
• Analytics Engineering — dbt modelling, 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 models across transactional, analytical, and semantic layers
• Deep expertise in modern data stack patterns: cloud data warehouses (Snowflake, BigQuery, Databricks), lakehouse architectures, dbt, data cataloguing tools
• Strong command of data modelling methodologies—dimensional modelling, Data Vault, OBT, and when to apply each
• Experience establishing or evolving data governance programmes 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 organisational boundaries without direct authority

It would be a bonus if you also had:

• Experience in a company with both a centralised 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 trade‑offs of every architectural choice.
• You lead through influence: You don't need a reporting line to drive alignment. You build credibility through expertise, communication, and a clear point of view.
• You're 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 trade‑offs, and ship real value while keeping the north star in view.

Benefits

• Competitive compensation, plus all full‑time employees participate in our ownership programme – 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 programmes 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 programme
• A culture rooted in inclusivity, support, and meaningful connection

Equal Opportunity Employer

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