Job Description: Our Data Operations team seeks a versatile engineer who enjoys working at the intersection of data engineering, software development, and DevOps/MLOps. This role involves working with data technologies, including distributed computing frameworks, alongside developing and managing common Python libraries, infrastructure automation, AI-related initiatives, and continuous integration/continuous deployment (CI/CD) workflows.
Responsibilities:
* Develop and optimize scalable data processing solutions using Python, SQL, and distributed data technologies.
* Design, develop, and maintain reusable Python libraries and APIs to enhance team efficiency.
* Contribute to AI and automation initiatives to streamline operations and improve workflow efficiency.
* Create and manage CI/CD processes, automating builds, tests, and deployments.
* Manage and automate data-related infrastructure tasks, such as resource provisioning, access controls, monitoring, and workspace management.
* Support future MLOps initiatives, ensuring robust operational deployment of machine learning workflows.
Required Skills:
* Proficiency in Python and its ecosystem, with a particular emphasis on data processing libraries and tools.
* Strong SQL for data querying, analysis, and optimization.
* Experience with cloud computing environments, preferably Azure, including services related to storage, identity management, and compute resources.
* Experience building automated CI/CD workflows and scripting in a DevOps environment.
* Knowledge of data infrastructure management practices.
* Familiarity with core DevOps principles and an interest in advancing into MLOps practices.
Compensation: $15/hour to $25/hour USD