Jobs via Dice
Cloud Architect OR Data Architect (Two roles)- BOTH H1B & - workable- 13+
Jobs via Dice, San Jose, California, United States, 95199
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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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
#J-18808-Ljbffr