HomeBigshyft Hiring for PayU Finance | Jobs | Data Engineering Lead |...

Bigshyft Hiring for PayU Finance | Jobs | Data Engineering Lead | BigDataKB.com | 09-02-22

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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