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Job Location: Mumbai
What You’ll do:
- Own the vision and execution for the infrastructure for a PayU’s fast growing mission critical Data-as-a-Service Platform
- Managing day to day operation and security of the data platform, with a focus developing and maintaining high-volume, low-latency data platform infrastructure especially for but not limited to consumption in machine learning applications
- Technical leadership for a team of 3 to 5 engineers
- Ensure the top-notch performance of data platform systems for customer-facing ML-based applications using latest opensource frameworks, highly available RESTful services, and back-end Cloud based/open source systems
- Manage execution of work while balancing priorities in coordination with the team leadership
- Create a long-term platform vision based on the latest technical landscape
- Support continuous improvement by investigating alternatives and technologies and presenting these for architectural review
What makes you a great fit:
- Advanced degree in computer science, engineering, mathematics, physics, or equivalent from Premier institutes
- 5+ years experience with developing scalable data platform architectures
- Experience with cloud-native software development methodologies, tools for application development/deployment stages including CI/CD
- Experience with Core Programming: Spark, Python/Java
- Experience with SQL, NoSQL, Cloud Computing (Any of AWS/Azure/GCP)
- Experience in Monitoring/Logging frameworks (ELK, Grafana)
- Experience in API integrations with third party APIs (Django/Flask/Falcon/web2py, etc)
- Good to have: Code-as-Infrastructure/Pipeline-as-Code (Terraform/Chef), Microservices with Springboot/Spring
- Ability to learn and work with emerging technologies, and solutions in Cloud/Open Source frameworks
- Good understanding and functional experience in Big Data Engineering: Data Warehousing, ingestion pipelines, data migration, QC.
- Good understanding and functional experience in Big Data Engineering practices: Data Warehousing, ingestion pipelines, ELT, data migration, QC
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