Principal, Cloud Data Platform Engineer

Tasks

• Improving the cloud platform through product development, design, platform development, and technology enablement
• Product development and design throughout the entire cycle (beta, MVP, and GA)
• Providing thought leadership and technical guidance for the product roadmap, feature changes, performance and security optimization, data-driven analytics, and machine learning
• Assess customers' business needs and collaborate with cross-functional product teams (Data, Product, Engineering, and Customer Success) to quickly make new products, services, or enhancements available to end customers
• Monitoring new technologies, emerging industry trends, and innovations, and sharing this information with key stakeholders
• Planning, designing, and describing the company's big data analysis needs
• Development, integration, and operation of data analysis, machine learning, and deep learning models
• Ensuring the robustness of these models and releasing them in a production-ready form
• Providing data and recommendation reports to share insights with senior management
• Documentation and Organization of Useful Data for Machine Learning and Data Science
• Collaborate with other data scientists, engineers, analysts, consultants, and subject matter experts to understand business opportunities, risks, and competitive threats
• Assessment of the Risks and Benefits of Data Projects and Products Within the Company and on Cloud Platforms
• Identification and optimization of models to be deployed in production
• Developing and coaching team members in the development and use of new technologies, tools, libraries, development environments, and new features
• Writing scripts and code to automate the deployment of network builds

Requirements

• Bachelor's degree in computer science, data engineering, or another technical field. A master's degree is preferred.
• 5+ years of relevant professional experience and experience in product development.
• 2+ years of experience in developing and maintaining data engineering and data science solutions on cloud platforms (GCP preferred).
• Proficiency in building, deploying, and maintaining data pipelines on AWS or GCP (preferred).
• Proficiency in data tools and programming languages for data science: PyTorch, TensorFlow, fast.ai, or similar.
• Strong statistical skills; familiarity with core statistical methods, including: ANOVA, chi-square, regression, confidence intervals, and p-values.
• Experience in data architecture and data modeling using SQL (preferred).
• A high level of interpersonal, communication, and collaboration skills.
• Familiarity with relational data models (SQL).
• Ability to work independently and deliver results with minimal supervision.
• Strong interest and experience with machine learning, Transformers, BERT, and embeddings.
• 5+ years of experience implementing large-scale machine learning frameworks.
• 3 to 5+ years of applied machine learning (experience in NLP and computer vision is a plus).
• Equivalent to 18 or more college credits in computer science, or a willingness to earn a BA/BS/MS in a technical field.
• Proficiency in scripting in at least one of the following programming languages: Python, Ruby, or Go.
• Expertise in at least one of the following product areas: cloud, virtualization, networking, or storage.