Data Engineer II

Textron is a renowned global multi-industry company with a diverse portfolio spanning aerospace and defense, specialized vehicles, turf care, and fuel systems. Our brand lineup includes leading names like Bell, Cessna, Beechcraft, E-Z-GO, Lycoming Engines and many others. With a strong worldwide presence and a workforce of 34,000 individuals across 25 countries, we prioritize attracting top talent. 

Job Summary:

As a Data Engineer II, you will play a key role in architecting, developing, and optimizing robust data infrastructure that empowers the organization’s data-driven initiatives. You will leverage your experience to lead complex data engineering projects, mentor junior team members, and drive continuous improvement of our data systems. In this role, you will collaborate with cross-functional teams including data scientists, analysts, and business stakeholders to ensure the delivery of high-quality, well-governed data assets that support strategic decision-making.

Job Responsibilities:

• Design, architect, and maintain scalable and resilient data pipelines for data ingestion, transformation, and delivery across multiple systems and platforms.
• Optimize existing data workflows for performance, reliability, and cost-effectiveness.
• Partner with stakeholders to gather requirements, analyze data needs, and translate business problems into effective data engineering solutions.
• Develop, implement, and enhance data validation, quality, and testing frameworks to ensure data accuracy, integrity, and consistency.
• Oversee the deployment and maintenance of data integration solutions, including ETL/ELT processes, real-time streaming, and batch processing.
• Contribute to the design and implementation of data models, storage solutions, and metadata management strategies.
• Ensure that all data systems comply with industry best practices, security guidelines, and regulatory standards.
• Mentor and provide technical guidance to Data Engineer I team members; promote knowledge sharing and best practices within the team.
• Troubleshoot complex data issues, identify root causes, and implement sustainable solutions.
• Stay current with emerging technologies, tools, and trends in data engineering, recommending and adopting new approaches as appropriate.
• Recommend ways to improve data reliability, efficiency and quality.
• Maintain proper version control for Engineering objects in DevOps environments.