Lead Azure Devops Engineer

We are hiring a Lead Azure DevOps Engineer with a strong technical background in application development and deployment pipelines, focusing on large-scale systems and trading databases. The role emphasizes DevOps skills and associated technical expertise to support critical research networks and trading databases.

The working day is based on Eastern Time (EST) (4 -6 hours).

Responsibilities

• Automate CI/CD pipelines and deployment workflows
• Manage and scale systems across 5–6 computers, ensuring stability and performance
• Handle SQL-based data processing and work with Redis for caching and storage optimization
• Develop and troubleshoot scripts using Python for operational needs, including decorators and system tasks
• Manage large-scale databases, traffic computation systems, and scaling solutions
• Design, improve, and maintain Azure DevOps environments and deployment strategies
• Operate within Linux environments, including Rocky Linux, to handle operational tasks
• Troubleshoot systems, build interfaces, stabilize systems, and reduce noise while delivering new features
• Collaborate with the data team on SQL-based systems and APIs
• Communicate directly with stakeholders in priority meetings 2-3 times weekly

Requirements

• 6+ years of professional experience and 1+ years of leadership experience
• Skills in automation with Ansible, Bash, and PowerShell
• Proficiency in Linux, including Rocky Linux and large-scale clusters, as well as Windows environments
• Capability to work in a fast-paced, lightly documented environment with proactive problem-solving skills
• Expertise in containerization using Docker
• Background in deployment pipelines and Azure DevOps
• Familiarity with system monitoring tools such as Grafana, Prometheus, or the ELK stack
• Knowledge of Git and security context
• High-level communication skills via Teams and Outlook
• Ability to thrive in a small startup environment, working closely with a dynamic team
• English proficiency at B2+ level

Nice to have

• Experience with traffic databases and compute systems utilized frequently across operations
• Familiarity with scaling and deployment pipelines for large-scale trading databases
• Understanding of the client's systems and workflows