Bachelor's degree in computer science or a related discipline or equivalent work experience required. 6 - 8 years of application or infrastructure related experience required experience in the securities or financial services industry is a plus 10+ years of experience in infrastructure engineering, DevOps, or site reliability roles. Hands-on experience with Kubernetes, Docker, HELM, and GitLab CI/CD. Proficiency in Python and Bash/Shell scripting for automation and operational tooling. Familiarity with enterprise tools such as JIRA, ServiceNow, and Azure AD. Working knowledge of networking fundamentals and storage systems, especially as they apply to distributed AI systems. Strong documentation and collaboration skills in a cross-functional, fast-paced environment. Willingness to participate in weekend or after-hours support rotations as needed. Educational Background: Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field. Technical Expertise: Proven experience in building and maintaining scalable data pipelines using tools such as Java, Python, SQL, DBT, Spark, Kafka, and Airflow. AI/ML Experience: Hands-on experience in deploying machine learning models into production environments, with a strong understanding of model lifecycle and performance optimization. Cloud & Big Data Proficiency: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies, Snowflake Communication Skills: Strong analytical and communication skills to translate complex data insights into actionable business strategies.
