Golang Expert System Architect
2 days ago
We are seeking a skilled Real-Time Data Processing Engineer to build and enhance scalable backend systems using Golang. This role involves migrating batch processing systems to real-time streaming architectures and developing robust data pipelines using Kafka or other streaming technologies. As a Real-Time Data Processing Engineer, you will work closely with other engineers, product teams, and stakeholders to deliver robust and scalable solutions.
Key Responsibilities:
- Develop and implement real-time streaming architectures using Golang.
- Collaborate with cross-functional teams to convert legacy batch processing systems into real-time streaming architectures.
- Implement, manage, and optimize data pipelines utilizing Kafka or other streaming technologies.
- Work with PostgreSQL to ensure high performance and reliability for data storage and access.
- Design, implement, and optimize GraphQL APIs for seamless data access and integration.
- Evaluate AWS services like Lambda, Fargate, SQS/SNS, and DynamoDB for optimization opportunities.
Estimated Salary: $130,000 - $190,000 per year
Required Qualifications:
- Golang Expertise: Strong proficiency in Golang with proven experience in building and maintaining backend systems.
- Real-Time Streaming: Hands-on experience with Kafka or other real-time streaming technologies.
- Database Management: Experience with PostgreSQL and solid knowledge of data modeling and best practices in database design.
- GraphQL: Familiarity with GraphQL or similar web API frameworks.
- DevOps: Proficiency in CI/CD processes, cloud infrastructure (AWS), and containerization tools such as Docker and Kubernetes.
- AWS Experience: Familiarity with AWS services like Lambda, Fargate, SQS/SNS, and DynamoDB.
Preferred Qualifications:
- Graph Databases: Familiarity with AWS Neptune or other graph databases.
- Microservices Architecture: Experience working with microservices architecture and distributed systems.
- Cloud Infrastructure: Experience with cloud infrastructure and deployment, particularly within AWS.
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