Minimum of five (5) years of experience with architecting and designing enterprise scalable Python applications. Experience with Machine Learning and Data Science methodologies preferred.
Familiarity with Big Data technologies (ex: HDFS, Hive, Spark, HBase, Kafka, Apache Beam, etc.)
Highly experienced with back-end programming languages and associated frameworks (ex: Python - Flask / Dask / Asynio etc.)
Experience implementing and integrating with RESTful API services in Python and building scalable and secure Python ML applications incorporating authentication and authorization dimensions.
Well versed in resiliency and scalability dimensions including instrumenting Python run time environment, web server configuration and elastic container infrastructure.
Experienced with deploying and managing elastic infrastructures based on Docker / Kubernetes footprint and cloud platforms such as Azure, AWS or Google Cloud Platform.
Experience implementing Python development best practices, modular and resilient assets, abstracting common capabilities as reusable libraries and well versed with various types of storage mechanisms ex: S3 bucket, Oracle DB, BigQuery etc.
Experienced in automated build and deployment pipelines including static scan analysis, code coverage through unit tests, ability to debug, triage and resolve functional and code optimization issues.
Experience with distributed version control systems and tools (Github/Git) and with automating application deployment, continuous delivery, and continuous integration (Jenkins)