- Understanding of broader technology landscape across Web, Mobile, Cloud, IoT, Big-Data and ML space.
- Practioner of software development best practices like Agile & iterative dev cycles, BDD, TDD, Code-Reviews (PRs), Automated CI/CD pipeline.
- Building solutions using event-driven microservices and cloud native architectures that are scalable using Docker and Kubernetes.
- Extensive experience with big data ETL and analytics applications based on PySpark and Hadoop technologies.
- Extensive experience with development and delivery of full-stack web and cross platform mobile applications.
- Hands-on with development technologies like Python, SQL/NoSQL DBs, PySpark, Pandas Hadoop, Hive, Kafka, NodeJS, ReactJS, Redux, C/C++, Linux/Unix.
- Hands on with testing frameworks like MochaJS, ChaiJS, SinonJS, Cypress, Behave (Cucumber), Pytest.
- Well versed with tools like Git, JIRA, NPM, PIP, Jenkins, Containers (Dockers), Kubernetes.
- Knowledge of Machine Learning (ML) landscape; Deep neural networks, Convolutional neural networks, Recurrent Neural networks, Re-enforcement learning, Keras, TesorFlow.