- Prior experience and in-depth understanding and experience working with a variety of legacy BI analytics and/or big data technologies (Hadoop, SQL/NoSQL/T-SQL databases, Teradata QueryGrid, BI tools, H2O etc).
- Strong knowledge and hands on experience of programming tools, scripting, and development languages and APIs (Python, C#, Bash, Jupyter, etc).
- Knowledge of DevOps and CI/CD automation tools-Git, Bamboo, Jenkins, etc.
- Knowledge of container technologies such as Docker and Kubernetes
- Strong working proficiency with Unix-based operating systems and general systems administration knowledge (i.e., command line interface, SSH, handling permissions, networking, resource utilization, etc); capable of Linux administration.
- Experience with Terraform is a must
- Comfortable discussing different authentication or authorization systems like LDAP, SAML, SSO, and Kerberos.
- Expert knowledge of Azure… also having working knowledge of AWS is a plus. Prior Dataiku Data Science Studio experience is ideal.
- Have a general understanding of data science and machine learning workflows and how the underlying data “flows” through the required environments / platforms to support these analytics.
- Prior experience managing technical software environment in the semi-conductor space a plus.
- Ability to develop and execute an operations strategy for incident and change management
- Ability to work with Azure, Dataiku Data Science Studio and other custom log files, create custom metrics, and incorporate these metrics into centralized analytics tools such as ELK, Splunk etc., to track ongoing cloud costs, compute consumption, storage consumption, etc
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