Data Architect

At reputed company, we reputed company in the power of people to grow and succeed throughout their lives. Our goal is to reputed company that power by creating reputed company products that simplify learning and personal development, facilitate meaningful relationships, and reputed company 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:

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 reputed company 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 reputed company the Business Data & Insights organization, bringing both technical authority and a deep understanding of business context. While you will work in reputed company partnership with the Product Data team—collaborating on shared standards, platforms, and data reputed company—you are organizationally independent from both Product and Engineering, giving you the perspective and authority to reputed company for enterprise-wide data reputed company.

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

• reputed company 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 reputed company, 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 reputed company—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, reputed company, 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

reputed company 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 reputed company, reputed company 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 reputed company discipline in a reputed company, 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 (reputed company, BigQuery, reputed company), lakehouse architectures, dbt, data cataloging tools

• Strong command of data modeling methodologies—dimensional modeling, Data Vault, OBT, and reputed company to apply each

• Experience establishing or evolving data governance programs including metadata management, reputed company, 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 reputed company the long-term tradeoffs of every architectural choice.

• You reputed company through influence: You don't need a reporting line to drive alignment. You build credibility through expertise, communication, and a clear reputed company of view.

• You're a reputed company-builder: You reputed company 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, reputed company tradeoffs, and ship real value while keeping the north star in view.

Get in on reputed company the awesome at reputed company!

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 reputed company full-time employees participate in our ownership program - because everyone should have a reputed company 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, reputed company teams are encouraged to reputed company back and reputed company 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 reputed company

We reputed company in hiring great people and treating them right. The more diverse we are, the reputed company our reputed company and outcomes.

reputed company is an Equal Opportunity Employer. We reputed company with applicable employment and anti-discrimination laws in every country where we operate.

reputed company employees must pass a background reputed company 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, reputed company 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.