Inherent Technologies
3 days ago – Be among the first 25 applicants
Location: San Jose, CA • Day 1 Onsite • EST Hours (Remote options available)
Role Overview Design and define enterprise data architectures for large‑scale systems. Lead data ingestion, transformation (ETL), and modeling for cloud‑based platforms. Architect foundational infrastructure for future AI/ML capabilities. Create detailed architecture diagrams and enterprise data models using Lucidchart or Visio.
Responsibilities
Design and evolve our company's cloud‑based data architecture.
Architect and oversee all stages of AI/ML pipeline development – ingestion, preprocessing, training, validation, deployment, monitoring, and lifecycle management within Azure.
Evaluate and select optimal cloud services, AI/ML platforms, and infrastructure components.
Design and scale distributed cloud solutions for real‑time and batch processing workloads with Kubernetes, managed ML platforms, and multi‑cloud strategies.
Implement automated build, test, and deployment pipelines (CI/CD) for machine learning models.
Establish security, compliance, and governance protocols for data access and privacy.
Translate business stakeholder needs into technical solutions and drive cross‑functional collaboration.
Monitor infrastructure and AI workloads, optimize resources, troubleshoot bottlenecks, and fine‑tune models.
Document architectural diagrams, policies, and best‑practice knowledge bases.
Lead pilots or proofs‑of‑concept for emerging technologies.
Required Qualifications
Bachelor's degree in Computer Science, Data Science, Information Systems, or related field.
Minimum 5 years of hands‑on data engineering experience using distributed computing approaches (Spark, Hadoop, Databricks).
Proven track record of designing and implementing cloud‑based data solutions in Azure.
Deep understanding of data modeling concepts and techniques.
Strong proficiency with relational and non‑relational database systems.
Exceptional diagramming skills with Visio or Lucidchart.
Preferred Qualifications
Advanced knowledge of Azure Data Lake, Azure Databricks, and other cloud‑specific data services.
Expertise in big data technologies (Hadoop, Spark).
Strong understanding of data security and governance principles.
Experience scripting in Python, SQL.
Cloud certifications (Azure/AWS) highly desirable.
Additional Skills
Exemplary written and verbal communication skills.
Outstanding analytical and problem‑solving ability.
Teamwork & leadership – ability to work effectively in cross‑functional teams.
Hands‑on Azure or AWS experience (either or both); GCP‑only experience is insufficient.
Proficient in Spark programming; Databricks experience a plus.
Understanding of architectural support for AI initiatives.
Referrals increase your chances of interviewing at Inherent Technologies by 2x.
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Location: San Jose, CA • Day 1 Onsite • EST Hours (Remote options available)
Role Overview Design and define enterprise data architectures for large‑scale systems. Lead data ingestion, transformation (ETL), and modeling for cloud‑based platforms. Architect foundational infrastructure for future AI/ML capabilities. Create detailed architecture diagrams and enterprise data models using Lucidchart or Visio.
Responsibilities
Design and evolve our company's cloud‑based data architecture.
Architect and oversee all stages of AI/ML pipeline development – ingestion, preprocessing, training, validation, deployment, monitoring, and lifecycle management within Azure.
Evaluate and select optimal cloud services, AI/ML platforms, and infrastructure components.
Design and scale distributed cloud solutions for real‑time and batch processing workloads with Kubernetes, managed ML platforms, and multi‑cloud strategies.
Implement automated build, test, and deployment pipelines (CI/CD) for machine learning models.
Establish security, compliance, and governance protocols for data access and privacy.
Translate business stakeholder needs into technical solutions and drive cross‑functional collaboration.
Monitor infrastructure and AI workloads, optimize resources, troubleshoot bottlenecks, and fine‑tune models.
Document architectural diagrams, policies, and best‑practice knowledge bases.
Lead pilots or proofs‑of‑concept for emerging technologies.
Required Qualifications
Bachelor's degree in Computer Science, Data Science, Information Systems, or related field.
Minimum 5 years of hands‑on data engineering experience using distributed computing approaches (Spark, Hadoop, Databricks).
Proven track record of designing and implementing cloud‑based data solutions in Azure.
Deep understanding of data modeling concepts and techniques.
Strong proficiency with relational and non‑relational database systems.
Exceptional diagramming skills with Visio or Lucidchart.
Preferred Qualifications
Advanced knowledge of Azure Data Lake, Azure Databricks, and other cloud‑specific data services.
Expertise in big data technologies (Hadoop, Spark).
Strong understanding of data security and governance principles.
Experience scripting in Python, SQL.
Cloud certifications (Azure/AWS) highly desirable.
Additional Skills
Exemplary written and verbal communication skills.
Outstanding analytical and problem‑solving ability.
Teamwork & leadership – ability to work effectively in cross‑functional teams.
Hands‑on Azure or AWS experience (either or both); GCP‑only experience is insufficient.
Proficient in Spark programming; Databricks experience a plus.
Understanding of architectural support for AI initiatives.
Referrals increase your chances of interviewing at Inherent Technologies by 2x.
#J-18808-Ljbffr