Data Architect

Data Architect IntelliTrans, (ITL), a subsidiary of Roper Technologies, Inc. is seeking a Data Architect to join our team hybrid in Atlanta, GA. Job Summary: The Data Architect will lead the strategic design and implementation of data architecture for IntelliTrans' Transportation Management Systems (TMS) platform and products. This senior role is responsible for the architecture, modeling, performance optimization, and governance of enterprise-scale data solutions that support multi-tenant SaaS operations serving global transportation and logistics customers. The Data Architect will collaborate with executive leadership, engineering teams, and business stakeholders to ensure our data infrastructure remains scalable, secure, performant, and aligned with business intelligence and operational requirements. This position requires deep technical expertise in data management combined with strategic thinking and strong leadership skills to guide the evolution of our data platform supporting mission-critical transportation operations worldwide. The Data Architect will set standards, define direction, and architect scalable solutionsparticularly around AWS, Databricks, AI, multi-tenant databases, data lakes, and real-time data streaming. Essential Duties and Responsibilities include the following. Other duties may be assigned. Define and communicate the overall data architecture strategy and roadmap for IntelliTrans' TMS platform, ensuring alignment with business objectives and analytics requirements Design and implement enterprise-scale data architectures for multi-tenant SaaS environments, including data warehousing, data lakes, and operational data stores Establish and enforce data architecture standards, data modeling best practices, and data governance policies across all development teams Lead the design of scalable data pipelines, ETL/ELT processes, and real-time data integration solutions to support transportation operations and business intelligence Collaborate with C-level executives, product management, and business stakeholders to translate data requirements into comprehensive technical solutions Oversee database design and optimization strategies for high-volume transactional systems and analytical workloads Guide technology selection decisions for data platforms, analytics tools, and emerging data technologies including AI/ML frameworks Lead data governance initiatives including data quality management, master data management, and metadata management programs Ensure data security, privacy compliance, and adherence to industry standards including GDPR, CCPA, SOC 2, and transportation industry regulations Design and implement data backup, recovery, and archival strategies for business-critical transportation data Drive adoption of modern data engineering practices including artificial intelligence, relational and NoSQL, graph databases, data mesh architecture, streaming analytics, and cloud-native data platforms Mentor & develop data engineers, database administrators, & analytics teams, fostering a culture of data excellence Direct performance tuning, capacity planning, and optimization of database systems and data platforms, including for Oracle and PostgreSQL databases. Represent IntelliTrans in technical forums and client discussions regarding data architecture and analytics capabilities Develop and maintain data architecture documentation, data dictionaries, and conceptual/logical/physical data models, including ER diagrams, dimensional models, and multi-tenant schemas. Lead technical due diligence for data-related acquisitions, partnerships, and technology investments Enable near real-time delivery of data changes directly to customers for consumption within their own data lakes. Architect and grow modern data lake and environments, ideally leveraging Databricks as the strategic platform Collaborate with engineering teams and offshore resources to deliver scalable, reliable, and well-governed data systems. Establish standards, best practices, and architectural patterns for enterprise data management. Build or enhance data platforms that support AI/ML workloads, including data readiness, optimization, and pipelines feeding AI models. Qualifications and Background Education: Master's degree in Computer Science, Data Science, Information Systems, or related technical field Industry certifications: AWS Certified Data Analytics or Database Specialty CDMP (Certified Data Management Professional) Oracle Database certifications Experience: Required Experience: Minimum of 10+ years of progressive experience in data management and architecture, with at least 5 years in senior data architecture leadership roles Databricks experience (required) strong working proficiency with at least 2-4 years strongly preferred. Deep AWS data ecosystem experience, including design and hands-on engineering with structured, unstructured, relational, and NoSQL data. Database expertise in Oracle and PostgreSQL including schema design, indexing, and performance tuning. Proven track record of designing and implementing large-scale data architectures for multi-tenant SaaS platforms serving enterprise customers Strong data modeling skills: ability to design optimal models and produce professional ER diagrams. Near-expert experience optimizing databases for performance and scalability. Strong understanding of multi-tenant architectures, including schema isolation and workload management. Experience with both OLTP and OLAP systems, including modern data warehousing and ETL/ELT patterns. Experience with CDC, data streaming, and queuing systems (e.g., Kafka, Kinesis, Pulsar). Ability to architect data sharing solutions enabling customers to ingest data in their own data lakes. Experience designing or supporting data pipelines optimized for AI/ML workloads, including feature engineering, vector storage, model-ready datasets, or integration with AI platforms (e.g., SageMaker, Databricks ML, or similar). Comprehensive understanding of data governance and security: Data Quality: Profiling, validation, monitoring frameworks Data Governance: Lineage tracking, data catalogs, metadata management Security: Encryption at rest/in transit, access controls, data masking, tokenization Experience with business intelligence and analytics tools: BI Platforms: Tableau, Power BI, Looker, or similar Reporting: SQL-based reporting, embedded analytics Understanding of DevOps practices for data platforms: Version Control: Git for database schemas and data pipelines CI/CD: Automated testing, deployment automation for data assets Infrastructure as Code: Terraform, CloudFormation for data infrastructure Preferred Qualifications: Experience building data lakes that support AI or advanced analytics. Experience designing data architectures that feed or support AI/ML models. Previous ownership of enterprise data strategy or acting as the primary data expert within an organization. Strong knowledge of cloud data platforms and services: AWS: RDS, Redshift, Aurora, DMS, Glue, Lake Formation, Athena Cloud Architecture: Multi-region replication, disaster recovery, data sovereignty Experience with AI/ML data architectures and feature stores Knowledge of AI-accelerated development and data analysis tools (Anthropic Claude Code, Microsoft Copilot) Experience with data science platforms and MLOps: SageMaker, Databricks, MLflow Feature engineering and model serving infrastructure Knowledge of API design for data services (RESTful, GraphQL) Experience in Transportation, Logistics, or Supply Chain Management systems Understanding of transportation industry data standards (EDI, API specifications) Experience with geospatial data and mapping technologies Performance Skills /Competencies: Exceptional strategic thinking and technology vision capabilities Strong executive presence and ability to communicate complex technical concepts to non-technical stakeholders Proven track record of building and leading high-performing technical teams Experience managing technical budgets and resource allocation Strong problem-solving skills with ability to balance technical excellence with business pragmatism Excellent written and verbal communication skills, including presentation and documentation abilities Ability to work effectively across global teams and different time zones Strong analytical and decision-making capabilities under pressure Polish