Data Architect
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
First seen 4d ago
No source stated a posting date, so this is when the listing first reached us — which is a floor, not the real age. Last seen at its source just now.
We have tracked this listing since 28 Oct 2026 (4 days). The employer's own board has carried it every time we have read it, most recently just now.
Is it remote?
Remote- USA
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay
$175k–195k/yr
Published by the source in its own salary field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Pinpoint employer's own board first seen 4d ago · last seen just now
The listing
This role will lead the design and evolution of our data architecture, enabling consistent, secure, and scalable access to data across our firms, enterprise systems, and digital products.
We need someone who can define the long-term data architecture while working directly with engineering teams to build solutions that deliver real business value.
Key Responsibilities
- Enterprise Data Architecture: Define and evolve the data architecture for the Trilon Digital Platform, ensuring scalability, security, reliability, and flexibility.
- Data Platform & Infrastructure: Design modern cloud-based data platforms, including data lakes, lakehouses, warehouses, and scalable data processing capabilities.
- Data Integration: Establish reusable patterns for ingesting, transforming, and integrating data from enterprise systems, engineering applications, and third-party sources.
- Data Modeling: Develop consistent enterprise data models, common definitions, and relationships across key business domains, including projects, clients, employees, financials, and engineering data.
- Data Quality & Governance: Establish practical standards for data quality, ownership, lineage, metadata management, and access controls in partnership with business and IT stakeholders.
- Data Products & APIs: Enable reusable, trusted datasets, data services, and APIs that support digital products, analytics, automation, and enterprise workflows.
- AI & Analytics Enablement: Design data architectures that support AI applications, enterprise knowledge retrieval, RAG, and advanced analytics.
- Technical Leadership: Work hands-on with data engineers and product teams on solution design, architecture reviews, technical decisions, and complex data challenges.
- Architecture Roadmap: Develop an incremental data architecture roadmap that balances immediate product needs with long-term enterprise data capabilities.
- Cross-Functional Collaboration: Partner closely with the Platform Architect, Product, Engineering, IT, and business stakeholders to align data investments with enterprise priorities and business outcomes.
Skills, Knowledge and Expertise
- 10+ years of experience in data engineering, data architecture, or related technical roles.
- Experience with Microsoft Azure, Databricks, Microsoft Fabric, Snowflake, or similar modern data platforms.
- Experience designing enterprise semantic models, master data management, and reusable data products.
- Experience supporting generative AI and enterprise knowledge platforms.
- Proven experience designing and implementing enterprise-scale cloud data platforms and modern data architectures.
- Strong expertise in data modeling, data integration, ETL/ELT pipelines, and distributed data processing.
- Hands-on experience with cloud data services, data lakes, warehouses, or lakehouse technologies.
- Strong SQL skills and experience with Python or other data engineering technologies.
- Experience integrating data from enterprise applications, APIs, databases, and third-party systems.
- Solid understanding of data governance, quality, metadata, lineage, security, and access management.
- Familiarity with AI/ML data requirements, including vector databases, embeddings, and RAG.
- Familiarity with AEC industry data and systems such as Deltek Vantagepoint, Autodesk, Esri ArcGIS, Bentley, or enterprise document management platforms is a plus
About Trilon
Pay Transparency