Job Description

At GE Aerospace Engineering, our customers challenge us with solving some of the worlds toughest problems. Our aerospace engineers rely on solutions architects to bridge their data and tools with the latest cloud and technology ecosystems, and how they can all be brought together to solve engineering problems. As a member of our team, you will sharpen your skills on cloud and enterprise architecture. You will gain expertise in cloud platforms, data engineering, data analytics, data science, and machine learning. In this role, you will identify use cases for Engineering, develop architectures and solutions using GE and cloud platforms, and build solutions to deliver strategic business value. You will partner with the team to build relationships with engineers and establish yourself as a trusted advisor. Our team culture thrives on collaboration and teamwork, and you will contribute your knowledge to our teams by participating as a subject matter expert.

The Impact You Will Have

• Provide technical leadership for engineers to evaluate and adopt Data and AI solutions.
• Consult on big data architecture, implement proof of concepts and solutions for business strategic projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications.
• Build and present reference architectures, technical guides, and demo applications.
• Provide escalated support for critical customer operational issues.
• Use your strengths to help your fellow team members, and drive cross-functional relationships across the company.
• Travel to team and customer location (20).

What We Look For

• Solution architects are customer-facing. Youll need to be comfortable communicating ideas to various audiences through presentations, whiteboarding, architecture discussions, and platform demonstrations.
• 3+ years in a customer-facing pre-sales, technical architecture, or consulting role.
• Experience designing and architecting distributed data systems.
• Comfortable programming in and debugging in Python, Java, SQL, and R.
• Have built solutions with public cloud providers, such as AWS, Azure, or GCP.
• Experience in at least one of the following: Data Warehousing (e.g., SQL, OLTP/OLAP/DSS), Data Science and Machine Learning technologies (e.g., pandas, scikit-learn).
• Degree in a quantitative discipline (e.g. Computer Science, Computer Engineering, Information Systems, Applied Mathematics).
• Nice to have: AWS and/or Azure Certification.

Additional Information