Lead DevOps Engineer

Position available on contract-to-hire or full-time employment. Local candidates preferred who are open to hybrid schedule estimated at 10-20% on-site.

Job Purpose: Work with various development groups to improve the efficiency and increase the reliability of our products and tools, and support optimal development processes within the group. We envision the person in this position to reduce the amount of time spent on code and infrastructure maintenance maintaining stable production environments, allowing technical teams to serve information more easily to stakeholders.

Essential Duties and Responsibilities:

• Develop and maintain internal software packages (Python, R), models and data science script build and release processes including continuous integration of software modules.
• Develop and maintain production data analysis jobs in partnership with data scientists and company analysts.
• Support tools utilized by analytics teams in the deployment and maintenance of services provided to external consumers of analytical information.
• Develop, document and communicate processes to technical teams.
• In collaboration with IT and Systems, design and maintain server environments and related administration for analytics teams use.
• Assist with the development and maintenance of automated tests and monitoring services to ensure continued reliability of our analytical products.
• Improve the overall efficiency of the R&D group and reliability of production models and code.
• Promote engineering best practices and standards.

Knowledge, Skills, and Abilities:

• 7+ working within a DevOps role with 1-2 years of lead responsibilities for on/off shore team delegation
• 2+ years working with Kubernetes, Rancher and RKE.
• Python, R, or similar programming languages, including for web development (Shiny, Angular ) and/or data analysis (Pandas).
• Well-versed working within Linux/Unix and Microsoft OS, Azure environments.
• Kubernetes and related technologies for virtualization.
• R Pro (the statistical computing environment).
• Experience guiding teams and migrating software to use Spark SQL, HPC, or other high volume data technologies.
• Azure DevOps, Nexus Repository System, and Gnu Make for setting up CI/CD pipelines.
• Azure cloud computing services or similar environments.
• Web services, micro services, REST APIs, and related software architecture concepts.