Senior AWS Cloud Data Engineer I

American Honda Motor Co., Inc. • Marysville, OH

3d • Onsite

About The Position

The Data Engineer designs, builds, and maintains scalable data solutions to enable advanced analytics and business intelligence across Honda’s enterprise.

Requirements

• A Bachelor's degree in Computer Science / Data Science / Applied Mathematics / Information Technology / Informations Sciences / Electronics or a related field of study or, equivalent relevant work experience.
• At least 3 years of demonstrable work experience in the industry, in data engineering or related roles.
• Proven track record in Amazon Web Services (AWS) based data solutions and orchestration
• Integration with ERP systems (SAP, Homegrown ERP Systems)
• API-based Data Exchange between Manufacturing, Supply Chain legacy applications and AWS pipelines
• Metadata Management for compliance attributes
• Audit Trails & Reporting for compliance verification
• Expertise in cloud to design, build, and maintain data-driven solutions
• Skilled in Data Architecture and Data Engineering with a strong background in Supply Chain domain
• Experienced in Data Modeling (Conceptual, Logical, and Physical), ETL optimizations, Query optimizations and Performance tuning
• Programming languages: Python, PySpark, SQL
• AWS Services: Glue, EMR, EC2, Lambda, DMS, S3, Redshift, RDS
• Data Governance: Informatica CDGC/CDQ
• DevOps Tools: Git, GitHub, AWS CDK
• Security: IAM, encryption policies
• Monitoring: CloudWatch, Glue Catalog, Athena
• Strong integration background with DB2, UDB, SQL Server etc
• Strong communication and collaboration skills.
• Ability to work with cross-functional teams and stakeholders.

Responsibilities

• Data Pipeline Development:
• Design and implement ETL pipelines using AWS services (Glue, EMR, DMS, S3, Redshift).
• Orchestrate workflows with AWS Step Functions, EventBridge, and Lambda.
• Integrate CI/CD pipelines with GitHub and AWS CDK for automated deployments.
• Data Modeling & Transformation:
• Develop conceptual, logical, and physical data models for operational and analytical systems.
• Optimize queries, normalize datasets, and apply performance tuning techniques.
• Use Python, PySpark, and SQL for data transformation and automation.
• Security & Governance:
• Implement IAM roles and encryption policies for data protection.
• Ensure compliance with governance standards using tools like Informatica CDGC/CDQ.
• Monitoring & Optimization:
• Monitor pipeline performance using CloudWatch and Glue job logs.
• Troubleshoot and resolve data quality and performance issues proactively.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees