Required Skills
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
- Minimum 6+ years of work experience
- Proven experience in building and managing large-scale distributed data processing systems.
- Strong experience with big data frameworks like Hadoop, Spark, Hive, Kafka, etc.
- Proficiency in data processing languages such as Python, Java, or Scala(Any one)
- Hands-on experience with cloud-based big data solutions (AWS, GCP, or Azure).
- Experience with data orchestration tools like Apache Airflow.
- Strong problem-solving skills and the ability to work in a fast-paced environment.
What you would do
- Design, develop and run cloud-native data platform and analytics SaaS services
- Hands-on coding>90% of the time
- Design and build large scale real-time stream processing systems
- Design, develop and run micro-services and analytics SaaS solutions
- Own Continuous Integration (CI) and Continuous Deployment (CD) for your services
- Own scalability, availability, and data security for your services
- Own tackle & resolve code defects
What you would need to succeed
- Are you passionate about building large scale multi-tenant cloud-native data platforms? Do you have prior experience in building data platform/data lake and analytics SaaS services in the public cloud.
- Come join our Data platform and Analytics team. This team owns, builds, and operates Guidewire’s cloud-native data platform and analytics SaaS offerings. Guidewire’s data platform is targeted to be best-in-class in enabling our customers with mission-critical insights and decision-making capabilities. The platform is designed to support all of our analytics, data science, and data applications. You will work in a highly collaborative environment building next-generation platforms and services.
- Design and develop scalable and high-performance data pipelines for collecting, processing, and storing large datasets.
- Work with Hadoop, Spark, Kafka, and other big data technologies to manage and process structured and unstructured data.
- Optimize and troubleshoot data pipelines for speed and efficiency.
- Collaborate with data scientists and analysts to integrate data-driven insights into business decision-making processes.
- Implement data security measures and maintain data integrity across the systems.
- Analyze and improve performance and scalability of data pipelines and storage solutions.
- Monitor and maintain data workflows, ensuring consistency and reliability.
- Work with cross-functional teams, including product, engineering, and operations, to understand and implement data requirements.
- Continuously evolve the data architecture to meet the future needs of the company.
- Preferred Skills:
- Experience with real-time data processing and streaming (e.g., using Apache Flink, Kafka Streams).
- Knowledge of containerization technologies like Docker and Kubernetes.
Bonus
- Soft Skills:
- Excellent communication and collaboration skills.
- Ability to work independently and as part of a team.
- Strong analytical mindset and attention to detail.
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