Job Description
As a DevOps Engineer, you will be the architect of our deployment and release ecosystems. Reporting to the AVP of Software Development, you will develop, document, and implement high-performance deployment and patch management processes. You will partner with Enterprise Systems Admins to automate solution deployments, drastically reducing risk and time-to-market across all supported environments.
Responsibilities:
- Pipeline Optimization: Improve and streamline the development lifecycle, including building, testing, integrating, and deploying software artifacts and infrastructure.
- Developer Enablement: Ensure the development team can deploy code with maximum speed, reliability, and security.
- Platform Collaboration: Work cross-functionally with Development and Infrastructure teams to maintain and enhance platform stability.
- Security \& Compliance: Partner with Information Security for audits, proactively implementing improvements and managing configurations within Change Management protocols.
- Cloud Leadership: Lead the strategic transition of software into the cloud, managing infrastructure services, monitoring, and databases.
- Operational Excellence: Resolve escalated issues and analyze incidents to minimize downtime, ensuring high-quality, durable systems are delivered on time and within budget.
- Innovation: Stay current on technology trends and provide expertise in scaling and architecting data-intensive applications.
Qualifications:
- Education:
University degree in Engineering, Science, or a related Quantitative discipline.
- Experience:
8–10 years of professional experience, specifically with complex, high-availability applications.
- Cloud Mastery:
Expert-level experience with Azure and distributed systems.
- Containerization:
Proven hands-on experience with Docker and Kubernetes.
- Automation Suite:
Proficiency with tools such as Jenkins, JFrog, and SCM tools like Git, BitBucket, or GitHub.
- Systems Programming:
Strong scripting skills (Bash/Shell) and an understanding of modern data architectures.
- Soft Skills:
Exceptional technical judgment, a team-oriented mindset, and the ability to prioritize tasks in a fast-paced, multi-task environment.