Engineer- Software, AI and Data Analytics

Honda Racing Corporation USA•East Liberty, OH

About The Position

The Software, AI and Data Analytics Engineer develops data-driven software solutions that support engineering analysis and decision-making. The role designs, builds, and maintains full-stack applications and data processes used to collect, store, process, visualize, and analyze information from sources such as wind tunnel testing, computational fluid dynamics (CFD), and track operations. The engineer translates engineering requests into software implementations, proposes and develops data-analysis and visualization methods, and maintains and improves existing software and processes. The role also supports test sessions through data collection, processing, quality checks, and reporting, and explores solutions to new problems to expand the team’s technical capabilities. The position requires collaboration in a fast-paced engineering environment. Working conditions may involve extensive travel and long periods of standing, walking, or sitting; working around vehicles, equipment, and other hazards; and physical tasks such as bending, crawling, lifting, and repetitive hand and wrist movements.

Requirements

Bachelor’s degree in Computer Science, Aerospace Engineering, Mechanical Engineering, or a related field, or five years of relevant professional experience.
One to three years of experience using programming, mathematical, or statistical methods to analyze data or improve operational efficiency.
Experience with full-stack software development, object-oriented design, databases, and data management.
Proficiency with Python and experience with data-analysis or visualization tools such as MATLAB, Power BI, Tableau, or Databricks.
Familiarity with frontend frameworks such as React or Angular and RESTful APIs.
Experience with version control, automated testing, and CI/CD practices.
Strong technical writing, communication, project coordination, and problem-solving skills.
Ability to work collaboratively and effectively in a fast-paced engineering environment.
Experience with C#/.NET, Python, and TypeScript.
Ability to make quick decisions, maintain hazard awareness, plan and solve problems, and cope with change and other people.
Ability to perform the physical demands described, including bending, kneeling, crawling, standing, sitting, walking, lifting objects weighing 25 pounds, and repetitive hand, wrist, or finger movements.
Ability to work around moving mechanical parts and vehicles, electrical current, high heat, and chemicals.

Nice To Haves

Knowledge of Apache Kafka, Apache Spark, or similar data-engineering technologies.
Experience with Microsoft SQL Server, Cosmos DB, MariaDB, or comparable database platforms.
Familiarity with Microsoft Azure, AWS, or Google Cloud.
Experience with motorsports, aerodynamic testing, wind tunnel data, CFD post-processing, aero maps, or track data systems.

Responsibilities

Translate engineering-group requests for data-analysis software into concrete full-stack implementations while following software engineering best practices.
Prepare materials for stakeholders describing expected project outcomes and timelines.
Propose and implement data-analysis and visualization methods, including methods for wind tunnel, CFD, and track correlation data.
Troubleshoot, debug, and upgrade existing software.
Participate in code reviews to maintain quality and share knowledge.
Support and develop existing processes to improve code quality, software robustness or flexibility, efficiency, efficacy, and insight from analytics products.
Create and maintain software documentation and document and report project and personal status.
Explore and develop solutions to new problems to expand the team’s technical capabilities.
Support wind tunnel, track, and other test sessions with data collection, processing, quality checks, and reporting.
Determine appropriate technical approaches and software solutions based on engineering requirements, data needs, and project objectives.
Recommend software architecture, tools, and technologies to improve scalability, reliability, and maintainability.
Prioritize technical solutions and improvements that enhance data processing, analysis, visualization, and engineering efficiency.