Senior DevOps Engineer Job Description
We are in search of a self-motivated and versatile senior devops engineer with the ability to work in an energetic and interactive environment. You must be a self-starter with a passion for crafting innovative software solutions. You will regularly learn and implement new technologies, and play an active role in developing, proving out, and (re)assessment of existing architectures.
ABOUT MOODY'S ANALYTICS MACHINE LEARNING TEAM
We are a team that creates and delivers machine learning models and applications for the financial services industry. At a high level, we ingest millions of news articles and other various data sources and process the data through pipelines to produce results such as entity recognition, sentiment analysis, credit adversity, and more.
Interested in machine learning? Take advantage of our growing team's collective knowledge and learn as you go. We fully embrace cross-training and continuous learning.
JOB RESPONSIBILITIES
- Deployment and productionisation or machine learning model applications in production.
- Lead the team in various aspects around stability, application delivery, and availability .
- Contribute to the growth of the team and continuous learning.
- Design and development of Terraform and Ansible modules.
- Maintain a strong security awareness through frequent assessments and software architecture design processes.
- Influence technology selection, software architecture design, security practices and implementation.
JOB REQUIREMENTS
- Extensive experience in DevOps engineering, team management, and collaboration.
- Be ready, willing, and able to work in a fast-paced environment with a strong desire to run to trouble.
- Proficiency in shell scripting, python, and HCL.
- Knowledge and experience working with distributed systems.
- Extensive knowledge &experience with git, linux system administration, docker, and databases including elasticsearch and MySQL.
- Kubernetes expert administrator with a security mindset.
- Capable of orchestrating service delivery across over 20 distributed kubernetes clusters.
- Extensive knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
- Strong communication and problem-solving skills with the ability to discuss projects with colleagues who have little technical knowledge of devops techniques and tools.
- Ability to oversee and provide significant valuable input regarding infrastructure design and maintenance.