Data Platform Engineer
Bengaluru · Senior
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Job description
Role: Data Platform Engineer – (Django Must- Big Data Platform)
Company: PayU
Location: Bangalore
Job responsibilities:
- Building, maintaining, and monitoring sustainable infrastructure with a focus on developing and maintaining high-volume, low-latency data platforms using latest opensource frameworks, highly available RESTful services, and back-end Cloud based/open source systems
- Execute day to day operation of the data platform to ensure top-notch performance of data platform systems for customer-facing applications
- Work on features to make the data Platform more robust and resilient
- Drive automation of application deployment for production environments
- Identify and support areas for process and efficiency improvement within platform operations
- Taking ownership of your projects, and have the work in small cross functional teams to drive projects to closure
- Highly collaborative with a strong belief in continuous improvement.
- Ability to stay focused and calm in a fast-paced environment.
Requirements to be successful in this role:
- BE/B-Tech/BS/Meng/MSc in computer science or a related technical field from top-tier colleges or equivalent practical experience
- 2.5-5 years of experience working on platform infrastructure based on Cloud and open-source systems and automation.
- Must be very good with programming lang : Python
- Django/Flask (preferred, must be experienced in building APIs)
- Databases: SQL querying & db understanding (RDBMS: mysql, postgresql; Nosql: mongodb, elasticsearch, dynamodb)
- Familiarity with big data tools & distributed systems (spark, redshift, kafka)
- Cloud Computing (Any of AWS/Azure/GCP), preferred: AWS
- Orchestration: airflow, docker
Good to Have:
- Monitoring/Logging frameworks (ELK, Grafana)
- Scalable Compute solutions (Kafka, Snowflake)
- Workflow management libraries and tools
- Container orchestration systems like Kubernetes
- Code-as-Infrastructure/Pipeline-as-Code (Terraform/Chef)
- Understanding and functional experience in Big Data Engineering practices: Data
- Warehousing, ingestion pipelines, ELT, data migration, QC
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