- Experience with deployments and provisioning automation tools (AWS Cloud formation, Ansible,
Docker, CI/CD (Gitlab), Kubernetes, or Helm charts
- 3+ years of programming experience (Python, Scala, etc).
- 3+ years of Big Data experience and deep understanding and application of modern data
processing technology stacks (Hadoop, Spark, Hive, Kafka, etc.).
- Deep understanding of streaming data architectures and technologies for real-time and low-
latency data processing (Kafka)
- Experience with data pipeline and workflow management tools such as Oozie or Airflow.
- Ability to drive adoption of Data Engineering best practices and sharing your knowledge.
- 1 year of recent experience in working with AWS is a must (EMR, Glue)
- Platform operations and Devops experience on AWS is preferred
Nice to haves:
- Experience with exposing API’s and API gateways
- Experience with Data Science tools such as Sagemaker, MLflow
- Experience with AWS Athena, IAM policies, Connectivity
- We expect that the engineer will bring his own device so he’s able to develop and test code on
his local machine.
- Our main language is English and should be fluent