Principal Data Architect

Description

This role can be filled remotely from Canada or the US.

The company is an applied AI engineering firm that builds AI agents for enterprise operations and delivers measurable results for clients. The team works mainly on AWS and pairs strong UX skills with senior engineers to get AI into production quickly and keep it running.

Founded in 2009, the firm has delivery centers in Canada, the United States, Eastern Europe, and Latin America. Its clients include companies in consumer products, retail, education, energy, financial services, healthcare, and manufacturing. Engineers here bring 15+ years of experience on average. The firm typically moves AI into production in 30 to 45 days.

This principal role sets data architecture direction across client work. You own the hardest data problems and act as the lead technical voice on how organizations model, move, govern, and trust data across warehouses, lakes, lakehouses, streaming systems, and the data foundations for AI and ML at scale.

You are the senior technical authority on data architecture. You guide data mesh, data product, and governance approaches, make high-stakes platform decisions, and shape the data behind production AI systems. You work with leaders and clients on strategy, mentor senior engineers and architects, and set a long-term data vision that stays scalable, secure, and gains value over time.

Responsibilities

• Set architecture standards for warehouses, data lakes, and lakehouses, covering medallion design and open table format choices.
• Shape governance for data and AI, including lineage, quality, cataloging, access control for AI agents, and evaluation data.
• Set the vision for batch and streaming systems and the orchestration that runs them.
• Guide enterprise data modeling across dimensional, Data Vault, data mesh, and data product approaches.
• Design the AI and ML data foundation, including feature stores, embeddings, vector stores, and pipelines for RAG and real-time retrieval.
• Build semantic layers, knowledge graphs, and pipelines for unstructured data such as documents, text, images, and audio so AI agents have reliable business context.
• Define infrastructure as code, CI/CD, and observability standards for building and running data platforms.
• Lead work on performance, scalability, cost, and reliability across the data estate.
• Own security, governance, and compliance across data assets, including GDPR, HIPAA, SOC2, PII handling, data residency, and audit readiness.
• Stay hands-on by prototyping, writing production code, and reviewing designs and pull requests with delivery teams.
• Use AI tools such as Claude, Cursor, and other assistants in daily work to raise quality and speed.
• Act as the lead technical voice for senior leadership and clients on data strategy and platform direction.
• Support pre-sales by shaping approaches, scoping, estimates, and proposals, and by joining client conversations.
• Explain complex data architecture clearly to both engineers and executives.
• Work with engineering, AI, analytics, and product teams to align data architecture with enterprise strategy.
• Set standards for architecture documentation, modeling, governance, and data contracts across teams.
• Define and champion architecture standards and best practices on the engagements you support.
• Build reusable accelerators, reference architectures, and templates that scale the practice and speed delivery.
• Mentor experienced engineers and architects to grow their technical judgment and impact.
• Take ownership of the hardest architecture and integration problems as the final technical decision-maker.
• Assess emerging technologies and recommend tools, frameworks, and patterns that improve architecture over time.

Requirements

• You act on problems you see and prefer making progress to waiting for certainty.
• You keep learning in a fast-changing AI field, even at a senior level.
• You give direct, honest feedback, including in hard conversations.
• You care about detail and ship work you would stand behind, even when it is not perfect.
• You take ownership, keep commitments, admit mistakes quickly, and back teammates when decisions are costly.
• You treat client businesses as your own and take the work seriously without taking yourself too seriously.
• You work well when budget, timeline, or team size is tight.
• You stay steady when scope, timelines, and stakeholders pull against each other, and you raise trade-offs early.
• You want to work alongside people who push each other to do better work.

Conditions

Remote work from Canada or the US.

Base salary range: $170,000 to $240,000 USD in the US, or $190,000 to $260,000 CAD in Canada. The posted range may change, and final pay may fall above or below it. Placement within the range depends on factors such as education, qualifications, certifications, experience, skills, seniority, geographic location, performance, shift, travel requirements, sales or revenue metrics, collective bargaining agreements, and business needs.

Benefits

• Paid time off.
• Medical, dental, and vision insurance.
• 401(k) or RRSP matching for eligible employees.