Introduction
A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe. You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio.
In this role you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers) where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
Your role and responsibilities
- Design develop and maintain scalable and efficient backend services using Python.
- Implement and manage Kafka-based messaging systems for real-time data ingestion processing and distribution.
- Build and maintain data pipelines and stream processing applications using Kafka Streams Kafka Connect or similar technologies.
- Collaborate with DevOps and Data Engineering teams to ensure seamless integration and deployment of services.
- Optimize application performance and scalability through profiling tuning and refactoring.
- Ensure high code quality through unit testing code reviews and adherence to software development best practices.
- Monitor and troubleshoot production issues related to Kafka and backend services.
Required education
Bachelor's Degree
Preferred education
Bachelor's Degree
Required technical and professional expertise
- Minimum 8 years of experience in Python development.
- Strong experience in building and maintaining Kafka-based systems.
- Proficiency in developing stream processing applications using Kafka Streams or Kafka Connect.
- Solid understanding of backend architecture RESTful APIs and microservices.
- Experience with CI/CD tools and deployment pipelines.
- Strong debugging and performance optimization skills.
- Familiarity with unit testing frameworks and code quality tools.
Preferred technical and professional experience
- Experience with cloud platforms (e.g. AWS Azure GCP).
- Exposure to containerization and orchestration tools like Docker and Kubernetes.
- Knowledge of data engineering concepts and tools.
- Experience with monitoring tools such as Prometheus Grafana or ELK stack.
- Familiarity with NoSQL databases caching systems and distributed computing.
- Contributions to open-source Python projects or active participation in developer communities.