Mitsubishi Logisnext Americas Inc.
Artificial Intelligence Data Architect and Engineer
About Us:
Logisnext Americas Inc. has supported customers for more than 100 years as a technology-driven forklift manufacturer. In addition to being a forklift manufacturer, we are also a total solutions provider offering scalable products and services from material handling and automation to extensive fleet support.
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. 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.
When & Where:
Hybrid Work Schedule: in the office 3 days a week. Travel less than 15%.
QualificationsWhat you need to have:
- 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
What we offer:
- 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
The specific salary for a successful candidate will depend upon, among other legitimate factors, education, training, and/or experience.
To be considered for this role, all applicants must submit a full and complete application through our careers page.
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.
Equal Opportunity Employer/Veterans/Disabled
Agency Disclaimer:
Logisnext Americas Inc. does not accept unsolicited resumes from third party vendors. Any unsolicited resumes from a third party will become the property of the company to use at the company’s discretion, with the understanding that Mitsubishi Logisnext Americas, Inc. will not be billed a fee for any such resumes. If a company is designated as an approved vendor, then said company can only provide assistance on those positions requested via a formal written agreement of support.
Similar Jobs
What you need to know about the NYC Tech Scene
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory



