Tool Box: AWS, RDS-Aurora MySql and Postgres, MongoDB-Atlas, Cassandra, BigQuery, ElasticSearch, Kafka, Redis, Memcached, Kubernetes, RabbitMQ, Prometheus, Grafana, Chef, Terraform, Jenkins, CircleCI, NodeJS, Kotlin, Groovy.
Data Stack: MySQL, Postgres, MongoDB, ElasticSearch, BigQuery, Redis and MemCached, both self-managed and their AWS counterparts.
What am I going to do?
Design, improve and maintain data infrastructure (Scale, Redundancy, Tuning, Backup, Setup, etc.)
Develop and adopt new tools to improve and optimize database performance.
Collaborate with developers to ensure services data efficiency and reliability.
3+ years managing noSQL databases: MongoDB or Cassandra
Experience in cloud environments – AWS is a big advantage
Understanding of core data structure and database concepts.
Deep understanding of data modeling and design patterns for document databases
Proved experience in monitoring, optimizing, and problem-solving production-grade databases
Working in a Linux environment and writing scripts in Python and Bash
Advantages:
Big advantage – Experience in Redis and ElasticSearch
Production experience with Public Cloud & container orchestration systems
Experience in data pipeline architecture
Experience with event streaming and messaging platforms such as Kafka and RabbitMQ.
Knowledge of CI/CD
Understanding of Kubernetes fundamentals
Development experience
