Product Engineer II - Data Management

Overview

Join our enterprise data management development team to build next-generation technologies that power server, desktop, and mobile applications working with rich spatial information models. We design and build scalable infrastructure for relational and NoSQL databases across Kubernetes, Linux, and Windows environments, with full support for high availability and disaster recovery. The team works on cutting-edge projects involving massive datasets, scalable architectures, AI-powered capabilities, and a diverse computational platform.

Responsibilities

• Work with users and industry experts to identify user requirements and customer workflows
• Work with top software engineers to envision, design, build, test, release, and support desktop and enterprise products
• Collaborate with software engineers, product engineers, and other stakeholders to build and test ArcGIS functionality related to databases, networks, and link analysis capabilities
• Work on building core data storage and management framework to support ArcGIS relational and NoSQL information models on premises or in the cloud. 
• Play a major part in the development process by determining product quality and release readiness

Requirements

• 2+ years of software testing experience
• Experience using an application development language, such as C++, C#, Java, JS, and/or Python
• Excellent written and verbal communication skills
• Familiarity with DBMSs & SQL
• Strong analytical and problem-solving skills
• Ability to manage priorities and tasks as needed in a fast-paced work environment
• Bachelor’s degree in computer science, engineering, GIS, data science, network science, mathematics, or related field

Recommended Qualifications

• Understanding of cloud platforms and services such as AWS S3, AWS RDS for PostgreSQL, Azure Blob Storage, and Azure Database for PostgreSQL
• Previous involvement in a large software development project
• Academic training in GIS and/or knowledge of GIS/Esri software
• Familiarity with Kubernetes, Docker, and/or cloud deployment technologies
• Master’s degree in computer science, engineering, or related field

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