Senior DevOps Engineer, Azure Cloud (hybrid)
About the position This is a temporary project role for a Senior DevOps Engineer specializing in Azure Cloud, with an estimated duration of 12 months and possible extensions. The position requires a hybrid work setting, with 3 days remote and 2 days onsite in Austin, TX (Mondays and Wednesdays required). Candidates must be able to relocate as required. The role involves providing end-to-end DevOps support, building scalable and secure data and AI pipelines, implementing CI/CD automation, and ensuring efficient deployment, monitoring, and performance optimization.
Responsibilities
- Provide end-to-end DevOps support including security, governance (RBAC), and collaboration with cross-functional teams to deliver reliable cloud and data solutions.
- Build scalable and secure data and AI pipelines.
- Implement CI/CD automation using Python and cloud infrastructure.
- Ensure efficient deployment, monitoring, and performance optimization.
- Analyze user requirements, procedures, and problems to automate processing or improve existing computer systems.
- Confer with personnel of organizational units to analyze current operational procedures, identify problems, and learn specific input and output requirements.
- Write detailed descriptions of user needs, program functions, and steps required to develop or modify computer programs.
Requirements
- Availability to work 2 days per week at the Client's site in Austin, TX.
- Experience with DevOps practices and tools (Azure DevOps, Git, CI/CD pipelines) (8 years).
- Experience with Microsoft Azure cloud platform (8 years).
- Experience with Snowflake administration including access control and security (RBAC, least privilege), performance tuning, and warehouse management (8 years).
- Experience with Python scripting for automation and data engineering tasks (8 years).
- Experience with Containerization and orchestration (AKS preferred) (8 years).
- Experience with Data pipelines, ETL processes, and cloud data integration (8 years).
- Experience with AI/ML concepts and platform integration (8 years).
- Experience with Azure Monitoring and Log Analytics including centralized logging, alerting, dashboarding, and security monitoring using audit logs and metrics (8 years).
- Experience with Monitoring, logging, and observability tools (8 years).
Nice-to-haves
- Experience with Implementing AI-enabled data platforms (e.g., Snowflake Cortex / ML pipelines) (3 years).
- Experience with Infrastructure as Code (3 years).
- Experience with Data security, compliance, and governance frameworks (3 years).
- Experience with Public sector or large enterprise environments (3 years).
- Strong problem-solving and analytical skills (2 years).
- Ability to manage multiple priorities in a fast-paced environment (2 years).
- Attention to detail and commitment to best practices (2 years).
- Experience with Snowflake AI / Cortex features (2 years).
- Excellent communication and documentation skills (1 year).