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Lead Software Engineer, Data Science
2 months ago
About the Role
We are seeking a highly skilled Senior Software Development Engineer to lead the development of our structured data streaming platform. As a key member of the Ring Data Science & Engineering team, you will be responsible for designing, building, and maintaining highly distributed components of our event streaming platform.
Key Responsibilities
- Design and implement highly scalable and performant software systems
- Drive the technical direction and architecture of complex software systems
- Identify opportunities to improve stability, performance, security, and cost of our services
- Deliver customer value in an iterative fashion while working towards longer term systems goals
- Make data-driven decisions to inform product prioritization
- Provide technical expertise throughout the product lifecycle and influence engineering best practices
- Participate in the hiring, coaching, and mentoring of engineers
About the Team
You will be joining a veteran team with several members who have 4+ years of experience at Ring and Amazon. Our team is responsible for delivering highly scalable, performant, and cost-effective solutions to simplify collection and processing of structured data for a variety of analytical use-cases.
Requirements
- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture of new and existing systems experience
- Experience as a mentor, tech lead, or leading an engineering team
- Strong analytical and problem-solving skills
Preferred Qualifications
- 5+ years of full software development life cycle experience
- Bachelor's degree in computer science or equivalent
- Experience working in an Agile environment following either Scrum or Kanban methodology
- Experience with modern CI/CD systems
- Experience with managing Kubernetes EKS clusters
- Experience with streaming data processing technologies such as Kafka, Amazon Kinesis, Spark, or Flink
- Experience with infrastructure-as-code using Terraform or CloudFormation/CDK
