seeking a Platform Architect with a strong focus on Data Architecture, Cloud Platform Strategy, and Enterprise Analytics Design to help define the future-state architecture of its modern freight technology ecosystem. As client migrates from its legacy logistics platform (AJEX) to a modern transportation platform environment, this individual will play a key role in designing how data flows across the organization, from source systems and integrations through transformation, storage, governance, reporting, and analytics.
This is a highly strategic architecture role focused on scalability, security, modernization, and long-term platform design rather than day-to-day development. The ideal candidate combines enterprise data platform architecture expertise with deep dimensional data modeling knowledge and can partner with both business and technical stakeholders to develop a sustainable, business-driven data strategy.
The environment is heavily centered on AWS and Databricks, with an emphasis on building modern cloud-native data platforms, lakehouse architectures, analytics solutions, and enterprise reporting capabilities.
Responsibilities
- Lead the architectural vision for client's cloud and data platform modernization initiatives.
- Define enterprise data architecture standards, governance frameworks, and platform design principles.
- Design scalable data platforms supporting integrations, reporting, business intelligence, and advanced analytics.
- Architect end-to-end data flows from operational source systems through transformation and consumption layers.
- Partner with business stakeholders to translate reporting and analytics requirements into scalable data solutions.
- Design and maintain enterprise analytical data models using dimensional modeling best practices.
- Create and govern fact tables, dimension tables, star schemas, and enterprise reporting structures.
- Define and manage SCD Type 1 and Type 2 strategies.
- Establish standards around data quality, lineage, metadata management, and governance.
- Collaborate with engineering teams on ETL/ELT architecture, pipeline design, and platform implementation.
- Guide modernization efforts involving Databricks, AWS, cloud-native analytics platforms, and enterprise integrations.
- Participate in architecture reviews and provide technical leadership on platform scalability, security, and performance.
- Ensure the platform is positioned to support future business growth and evolving freight technology needs.
Required Skills & Experience
Data & Platform Architecture
- Strong experience with enterprise Data Architecture and Data Platform Architecture.
- Experience designing cloud-based data platforms and modern analytics ecosystems.
- Proven experience leading large-scale modernization, migration, or transformation initiatives.
- Strong understanding of enterprise integration architecture and data movement strategies.
- Experience with data governance, lineage, metadata management, and security best practices.
Data Modeling & Analytics
- Advanced expertise in dimensional data modeling.
- Strong experience designing fact tables and dimension tables.
- Expertise with star schema architecture.
- Experience implementing Slowly Changing Dimensions (SCD Type 1 & Type 2).
- Strong understanding of enterprise reporting and Business Intelligence environments.
- Ability to translate business requirements into scalable analytical data models.
Cloud & Engineering
- Hands-on experience with Databricks.
- Strong experience within AWS environments.
- Experience designing and supporting ETL/ELT frameworks.
- Experience building scalable data pipelines and integration architectures.
- Strong SQL skills.
Preferred Skills
- PySpark experience.
- Python and Spark knowledge.
- Modern Lakehouse and Data Lake architecture experience.
- CI/CD and DevOps exposure.
- Infrastructure-as-Code experience.
- Experience in logistics, transportation, supply chain, or freight technology environments.
- Familiarity with AJEX, Transfix, or similar transportation management platforms.
- Experience supporting enterprise BI, analytics, and reporting initiatives.
What Success Looks Like
This person will own the architectural roadmap for client's next-generation data platform while helping guide the migration from legacy logistics systems into a modern AWS and Databricks ecosystem. They will balance business requirements, analytics needs, governance standards, and technical scalability while ensuring the organization has a strong foundation for reporting, integrations, data quality, and future growth.
Ideal Background
Look for candidates who have:
- Data Platform Architect
- Enterprise Data Architect
- BI Architect
- Analytics Architect
- Data Modeling Architect
- Cloud Data Architect
- Principal Data Architect
- Lakehouse Architect
- Databricks Architect
- Solution Architect (Data)
Must-Have Keywords: Databricks, AWS, Data Architecture, Data Modeling, Star Schema, Fact Tables, Dimension Tables, SCD Type 1, SCD Type 2, ETL, ELT, Data Governance, Data Lineage, Lakehouse, Enterprise Analytics, BI Architecture, Cloud Migration, Data Pipelines.
Highest Signal Candidates: Architects who have designed enterprise-scale AWS/Databricks environments and can speak equally well about platform strategy, dimensional modeling, governance, and modernization efforts.