Data Architect
Listed on 2026-09-06
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IT/Tech
Data Engineering, Data Warehousing
Tricon is an owner, operator and developer of single-family rental homes in the U.S. and multi-family apartments in Canada. Our commitment to enriching the lives of our employees, residents and local communities underpins Tricon’s culture and business philosophy. We provide high-quality rental housing options for families across the United States and Canada through our technology-enabled operating platform and dedicated on-the-ground operating teams.
Our development programs are also delivering thousands of new rental homes and apartments as part of our commitment to help solve the housing supply shortage.
The Data Architect owns the foundational design of the data platform, from how raw data enters the warehouse to how it surfaces as trusted metrics in business tools, covering the full stack: ingestion design, bronze-to-gold medallion layer structure, transformation standards, orchestration patterns, and the semantic layer that business users interact with. The Data Architect is responsible for platform health - reliability, cost, performance, and broader platform design.
They work alongside the North American and Indian Operations engineering teams as the primary technical authority, setting direction, reviewing work, and escalating complex problems. The Data Architect also works with the governance function to make sure the platform is traceable and controlled, and with the enterprise program management office to scope requirements when major initiatives have a data component.
Essential Duties and Responsibilities include the following but are not limited to the job specifications contained herein. Additional duties or job functions that can be performed safely may be performed as deemed necessary by supervisory personnel.
Own the architecture of the data platform end-to-end: warehouse design, medallion layer conventions (bronze, silver, gold), transformation standards, orchestration patterns, and semantic layer governance. Define what each medallion layer means in practice: what lands in bronze as raw source data, what gets cleaned and conformed in silver, what gets shaped into business-ready models in gold, and hold those boundaries consistently as the platform evolves.
Own platform health: track and manage compute costs, query performance, pipeline reliability, and model freshness. Identify degradation before it reaches business users. Set ingestion standards for new data sources: landing zone design, schema evolution handling, change detection patterns, and failure recovery approaches. Serve as the technical escalation point for the India Operations engineering team. Conduct architecture reviews, provide design guidance, and review code for pattern compliance.
Maintain platform documentation: architecture decision records, data flow diagrams, runbooks, and post-incident reviews. Evaluate new tools and approaches and own the technical roadmap for platform infrastructure. Partner with Data Governance on quality enforcement, lineage tracking, and access control design across the warehouse and downstream tools. Define and maintain the semantic layer, a single authoritative definition of business metrics that any report or analyst can rely on.
Partner with analytics and BI teams to validate the semantic layer reflects how the business asks questions and define row-level security and access patterns that control metric exposure by role. Get involved early in cross-functional projects to help shape data requirements and platform needs before implementation begins, rather than inheriting decisions after the fact. Sit on the Technical Review Board, evaluating major architectural decisions and engineering practices for consistency with platform standards before they are implemented.
Define and maintain enterprise data standards - naming conventions, documentation requirements, and data quality benchmarks - that apply consistently across the platform. Own the role-based access control (RBAC) design across the warehouse, defining role hierarchies, privilege tiers, and access patterns that balance self-serve analytics with data security…
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