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# Artificial Intelligence Data Architect and Engineer

- **Company:** Mitsubishi Logisnext Americas Group Inc.
- **Location:** Grand Rapids, MI, United States
- **Experience:** Expert
- **Salary:** $130,000.0 - $160,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Microsoft Azure, Big Data, Information Systems, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Structures, DevOps, JSON, Python (Programming Language), Machine Learning, Operational Data Store, DataOps, SQL Databases, Data Streaming, Enterprise Data Management, Cloud Platform System, Data Ingestion, Azure Data Factory, Snowflake, Database Optimization, Generative AI, HybridCloud, Data Strategy, Information Technology, Integration Frameworks, Apache Kafka, Operational Systems, Data Management, Multiaccess Edge Computing, Virtual Agents, Api Design, Data Pipelines, Databricks
- **Published:** July 4, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=9442e33d8fc54bc7

## About the Role

* 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, Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time.

## Description

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. The ideal candidate combines strong data-engineering execution skills with architectural thinking and experience working with industrial IoT, telemetry, and other high-volume machine-generated data. This role requires a balance of strategic design leadership and roll-up-your-sleeves implementation.
What you will do:

 * 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.


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