IT Manager - Platform Engineering & Data Science
New
J
JobgetherInformation Technology
United StatesFull-TimeManager
SalaryEstimated monthly salary range of approximately $7,568.91 to $13,247.76
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Job Details
- Experience
- Minimum of 5 years of hands-on experience in platform engineering
- Required Skills
- PythonGCPJavaSoftware ArchitectureCI/CDBigQueryMLOps
Requirements
- Bachelor’s degree in information technology, computer science, or a related field preferred, or equivalent professional experience.
- Minimum of 5 years of hands-on experience in platform engineering, including experience supporting machine learning implementations and data analytics enablement.
- Proven experience leading engineering or technical teams, including performance management and career development.
- Strong programming experience with Java and/or Python, combined with software architecture and engineering expertise.
- Experience implementing secure software delivery practices, DevSecOps, CI/CD pipelines, and automation frameworks.
- Hands-on experience designing and operating cloud platforms, particularly Google Cloud Platform (GCP), with knowledge of Azure hybrid-cloud environments.
- Experience enabling data science and machine learning workflows using cloud-native tools such as Vertex AI, BigQuery, or similar technologies.
- Familiarity with operational monitoring, telemetry, alerting, and application performance management solutions.
- Strong understanding of software design patterns, modern engineering standards, and scalable architecture practices.
- Ability to contribute hands-on alongside engineers, architects, data scientists, and quality teams.
- Strong leadership, communication, presentation, and stakeholder management skills.
- Self-motivated mindset with the ability to identify opportunities, solve complex problems, and drive initiatives independently.
Responsibilities
- Lead, mentor, and develop a high-performing team of platform engineers, architects, and technical specialists.
- Define and execute platform engineering, cloud, and data science roadmaps aligned with technology and business objectives.
- Design, build, and optimize scalable platform capabilities across Google Cloud Platform (GCP) and hybrid-cloud environments.
- Partner with AI engineering, data science, product, architecture, and IT teams to enable machine learning and software delivery initiatives.
- Drive DevSecOps practices, CI/CD automation, infrastructure improvements, and platform reliability standards.
- Own and enhance MLOps capabilities supporting model development, deployment, monitoring, and scaling.
- Establish engineering standards, architecture patterns, API strategies, and reusable platform services.
- Lead cloud modernization initiatives, automation efforts, developer experience improvements, and technology transformation projects.
- Manage project execution, budgets, vendor relationships, and team capacity planning.
- Monitor platform performance, security, availability, and scalability while proactively addressing risks.
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