Role: DevOps Engineer, Corporate Banking

Join our Data & Technology Services team as a DevOps Engineer and play a pivotal role in deploying and managing infrastructure that supports advanced AI & ML engagements for the investment banking sector. You will be instrumental in automating and optimizing our operations and development processes, ensuring seamless, scalable, and efficient delivery of services. Your primary duties will encompass:

• Deploying and managing cloud infrastructure to enable and support data storage, processing, and MLOps.
• Developing CI/CD pipelines to build and maintain continuous integration and continuous deployment pipelines to automate software and AI/ML model delivery and infrastructure changes.
• Managing code repositories to ensure proper version control and collaboration using tools such as Git.
• Set up monitoring tools to track performance and troubleshoot issues, ensuring availability and scalability.
• Collaboration with data teams by working closely with data scientists and data engineers to automate data pipelines and integrate machine learning models into production environments.
• Implement security best practices and ensure compliance with industry standards.
• Create detailed documentation of processes and provide training to internal teams on DevOps and MLOps practices.
• Managing client relationships, effectively communicating with stakeholders, and ensuring the delivery of high-quality solutions.

Experience / Skills

5+ years of relevant experience in:

• Experience in a DevOps role, preferably within the financial services industry.
• Strong experience with Azure cloud platform
• Experience with Azure services i.e. Azure Data Factory, Databricks, Unity Catalog.
• Experience with CI/CD tools such as Jenkins, GitLab CI, or Azure DevOps.
• Proficiency in scripting and automation using Python, Bash, or PowerShell.
• Knowledge of containerization and orchestration tools such as Docker and Kubernetes.
• Strong understanding of networking, security, and infrastructure management.
• Strong communication skills, both written and oral, with a business and technical aptitude.

Additionally, desired skills:

• Experience with MLOps technologies e.g. MLFlow
• Familiarity with Spark technologies e.g., PySpark.
• Data Analytical and AI/ML experience or skills.
• Knowledge of financial securities and asset classes.

Education

• Bachelors or Masters in Science or Engineering disciplines such as Computer Science, Engineering, Mathematics, Physics, etc.