We are looking for a hands-on Principal Data Architect to help shape and build the enterprise data foundation for the Trilon Digital Platform.
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.
The ideal candidate combines deep expertise in modern data platforms, data modeling, integration, and governance with a practical, delivery-oriented mindset.
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.
- 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.
- 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
Trilon was formed with the vision of building the next Top 20 infrastructure consulting firm in North America by bringing together some of the nation’s best infrastructure consulting firms, focused on delivering practical and sustainable infrastructure solutions. Trilon is backed by Alpine Investors, a PeopleFirst Private Equity Firm. Trilon currently comprises 5,500+ staff across the US. For more information, visit www.trilon.com.
Pay Transparency
Pay Transparency
The base salary range for this role is indicated in the posting. This range reflects the company’s good faith estimate of the compensation for this position at the time of posting. Final compensation will be determined based on factors such as experience, skills, qualifications, internal equity, and geographic location.