Cloud Architect OR Data Architect (Two roles)- BOTH H1B & - workable- 13+

Title

Cloud Architect and Data Architect (Two roles)

Location

San Jose, CA (hybrid) 3 days onsite 2 days remote (Only Local to California)

Note

Bachelor's degree - B.Tech in Computer Science Required

Responsibilities

• Design, evolve, and optimize the company’s cloud‑based data architecture.
• Align AI and ML system design with broader business objectives, shaping technology roadmaps and architectural standards for end‑to‑end cloud‑driven analytics and AI adoption.
• Architect and oversee all stages of AI/ML pipeline development: data ingestion, preprocessing, model training, validation, deployment, monitoring, and lifecycle management within cloud environments.
• Evaluate and choose optimal cloud services, AI/ML platforms, infrastructure components (compute, storage, orchestration), frameworks, and tools that fit operational, financial, and security requirements.
• Design and scale distributed cloud solutions capable of supporting real‑time and batch processing workloads for AI/ML, leveraging technologies like Kubernetes, managed ML platforms, and hybrid/multi‑cloud strategies for optimal performance.
• Implement automated build, test, and deployment pipelines for machine learning models, facilitating continuous delivery, rapid prototyping, and agile transformation for data and AI‑driven products.
• Establish robust protocols for data access, privacy, encryption, and regulatory compliance (e.g., GDPR, ethical AI), coordinating with security experts to continuously assess risks and enforce governance.
• Serve as the liaison between business stakeholders, development teams, and data scientists, translating company needs into technical solutions, and driving alignment and innovation across departments.
• Monitor infrastructure and AI workloads, optimize resource allocation, troubleshoot bottlenecks, and fine‑tune models and platforms for reliability and cost‑efficiency at scale.
• Create and maintain architectural diagrams, policy documentation, and knowledge bases for AI/ML and cloud infrastructure, fostering a culture of transparency, learning, and continuous improvement.
• Stay abreast of new technologies, frameworks, trends in AI, ML, and cloud computing, evaluate emerging approaches, and lead strategic pilots or proofs‑of‑concept for next‑generation solutions.
• Must work EST hours.

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field.
• Minimum of 5 years of hands‑on data engineering experience using distributed computing approaches (Spark, Map Reduce, Databricks).
• Proven track record of successfully designing and implementing cloud‑based data solutions in Azure.
• Deep understanding of data modeling concepts and techniques.
• Strong proficiency with database systems (relational and non‑relational).
• Exceptional diagramming skills with tools like Visio, Lucidchart, or other data visualization software.

Preferred Qualifications

• Advanced knowledge of cloud‑specific data services (e.g., Databricks, Azure Data Lake).
• Expertise in big data technologies (e.g., Hadoop, Spark).
• Strong understanding of data security and governance principles.
• Experience in scripting languages (Python, SQL).

Additional Skills

• Exemplary written and verbal communication skills to collaborate effectively with all teams and stakeholders.
• Outstanding analytical and problem‑solving skills for complex data challenges.
• Ability to work effectively in cross‑functional teams and demonstrate potential for technical leadership.

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Engineering and Information Technology

Industries

Software Development

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