Artificial Intelligence Data Architect and Engineer

About the role

The AI Data Architect & Engineer plays a critical role in building and scaling the company’s long-term data and AI capabilities. This dual-role position is responsible for both architecting enterprise-grade data platforms and hands-on development of data pipelines and integrations that support telematics, operational systems, analytics, predictive maintenance, and AI-driven applications.

Responsibilities

• Design, implement, and evolve a scalable enterprise data architecture that supports telematics, operational, and enterprise data, including foundational data models, schemas, integration frameworks, and lakehouse architectures, while ensuring performance, reliability, cost efficiency, and scalability.
• Build, maintain, and optimize cloud-based data pipelines and large-scale data processing workflows to support analytics, AI, and enterprise reporting needs.
• Develop and manage ingestion pipelines for high-volume streaming and batch telemetry data from forklifts, sensors, gateways, APIs, and edge devices, ensuring reliable, scalable, and standardized data capture.
• Integrate data across enterprise systems including ERP, CRM, service management, parts and warranty systems, and vendor telematics platforms, while supporting master data alignment across assets, customers, equipment, and locations.
• Standardize, normalize, enrich, and prepare machine-generated and operational data to support predictive maintenance, operational intelligence, predictive analytics, and generative AI or RAG-based applications.
• Collaborate with IT, Analytics, Product Management, Service teams, and third-party vendors to translate business and operational requirements into scalable technical solutions, data integrations, and long-term data strategy contributions.
• Partner with internal technology stakeholders to support data governance, security, access controls, observability, DevOps/DataOps practices, and ongoing optimization of platform performance and cloud costs.

Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field
• 7+ years of experience in data engineering, data architecture, or cloud-based data platforms
• Strong proficiency in SQL and Python
• Proven experience building and supporting ETL/ELT pipelines and large-scale data processing workflows
• Hands-on experience with cloud platforms, with Microsoft Azure preferred
• Experience working with modern data platforms such as Databricks, Snowflake, Azure Data Factory, and/or Kafka or other event streaming technology
• Strong understanding of data modeling, schema design, database optimization, and data integration patterns
• Experience working with APIs, JSON, streaming data, and IoT or telematics data structures

What would be nice to have

• Experience in industrial equipment, fleet management, logistics, manufacturing, automotive telematics, or IoT platforms
• Familiarity with predictive maintenance, condition monitoring, or asset optimization concepts
• Experience supporting machine learning or AI-driven applications
• Exposure to edge computing or hybrid cloud and edge architectures
• Experience working with data governance considerations across multiple geographic regions, including North America and Europe
• Prior collaboration with third-party vendors or OEMs on data integrations and platform implementations

Benefits

• Medical, dental, and vision benefits
• Paid Vacation, Sick Time, and Paid Holidays
• Profit Sharing Opportunities
• Flexible Spending and HSA Accounts
• 401k with automatic company contribution and company match
• Short-term and long-term disability insurance
• Life, Dependent Life, and AD&D Insurance
• Paid Parental Leave (Includes 6-8 weeks of maternity leave and 5 days of paternity leave)
• Employee Assistance Program
• Employee Discounts
• On-site fitness center (Houston)
• On-the-job training and development

Schedule

A Hybrid Work Schedule: in the office 3 days a week. Travel less than 15%.