Principal Software Engineer
Indexed description
Create a positive and lasting impact on the business while building an exciting career full of meaningful work. You will find the support, coaching, and training you need to excel at your role. Our culture of innovation means your ideas will be heard!
Be a part of a dynamic software development group at Verisk Catastrophe and Risk Solution, contributing to design and development of scalable analytic solution with high performance. You are expected to work in an agile team to plan and design new features, write clean, testable, and performant code, and create automatic tests.
Responsibilities
- Translate requirements and architecture to designs and working software
- Provide technical leadership to teammates via day-to-day collaboration along with design and code reviews
- Develop cloud-based analytical framework, algorithms, and tooling
- Contribute to testing, CI, and DevOps infrastructure
- Focus on performance, cost efficiency, and stability as well as functionality
- Evolve the use of AI to improve development outcomes.
- BS Degree required in Computer Science. MS Degree preferred. Equivalent experience considered.
- 10+ years in commercial-grade software development, specializing in backend business logic, frameworks, scalability and performance aspects of the system
- Strong understanding of object-oriented program, design patterns, and coding for testability.
- Competency to expertise in a combination of C#, Angular, PostGresSql, Python, or strongly translatable skill.
- Current cloud proficiencies including infrastructure as code and containerization. AWS preferred.
- Enthusiastic, passionate, and quick learner with strong written and verbal communication skills.
- Possess a positive attitude and the ability to multi-task, stay organized in a dynamic teamwork environment, and have an attitude to get things done.
- AWS platform development.
- C#, Angular, Python, SQL
- PostGres, Glue, Aurora
- Background in algorithms, high-performance distributed and parallel computing
- Knowledge of code analysis and performance-tunning tools
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