Cloud Solutions Architect 3

Responsibilities

• Directs the architectural aspects of a cloud brokering team across all aspects of IT and the business.
• Planning and engineering of an organization's cloud computing infrastructure and applications.
• Implementing and designing hardware and software.
• Familiar with standard concepts, practices, and procedures of cloud technology, including Software as Service (SaaS), Platform as Service (PaaS), or Infrastructure as a Service (IaaS).
• Supports a regulated, multi-cloud enterprise environment, requiring expertise in data/AI platforms, vendor coordination, monitoring, and 24×7 operations, while ensuring security, compliance, and system reliability.

Requirements

• Minimum 8 years of experience in multi-cloud platform expertise (Azure + GCP).
• Minimum 8 years of experience in GenAI & Enterprise AI Platform Knowledge (Gemini, Vertex AI).
• Minimum 8 years of experience in Azure Monitor, Log Analytics, GCP Cloud Monitoring, and logging frameworks to track performance, reliability, and usage.
• Minimum 8 years of experience using Logstash for log ingestion, transformation, and integration with Azure Log Analytics for proactive monitoring and alerting.
• Minimum 8 years of hands-on experience supporting data pipelines, data platforms, and analytics workloads in enterprise environments.
• Minimum 8 years of experience with Informatica Cloud (IICS), Secure Agents, APIs, and integration patterns, including handling monitoring and integration challenges.
• Minimum 8 years of strong implementation of IAM (least privilege), network security, audit logging, and compliance (FedRAMP/regulated env.).
• Minimum 3 years of familiarity building and managing Tableau Cloud environments.
• Minimum 3 years of experience integrating ArcGIS or geospatial data systems with cloud data platforms.
• Minimum 3 years of knowledge of scripting (Python, Bash) and automation (serverless, CI/CD pipelines).
• Minimum 3 years of exposure to GKE, AKS, Docker, and microservices architectures.
• Minimum 3 years of knowledge of data mesh, ETL/ELT architectures, API integrations, and enterprise data standards.
• Minimum 3 years of strong analytical thinking to assess platform issues, make timely architectural decisions, and drive resolution in high-pressure environments.
• Minimum 3 years of ability to take end-to-end ownership of platform stability, reliability, and delivery, proactively identifying risks and driving outcomes.
• Minimum 2 years of ability to clearly translate complex technical concepts into business-friendly language and actively engage with stakeholders, leadership, and end users.
• Minimum 2 years of proven ability to lead and coordinate across engineering, data, infrastructure, and business teams, ensuring alignment and delivery of platform initiatives.

Candidate Skills

• Expertise in Azure Monitor, Log Analytics, GCP Cloud Monitoring, and logging frameworks to track performance, reliability, and usage.
• Experience using Logstash for log ingestion, transformation, and integration with Azure Log Analytics for proactive monitoring and alerting.
• Ability to design alerting solutions using Twilio (SMS/voice) for ETL failures and operational notifications.
• Experience with Blob Storage, Data Lakes, and structured storage systems enabling analytics and AI workloads.
• Hands-on experience supporting data pipelines, data platforms, and analytics workloads in enterprise environments.
• Experience with Informatica Cloud (IICS), Secure Agents, APIs, and integration patterns, including handling monitoring and integration challenges.
• Strong implementation of IAM (least privilege), network security, audit logging, and compliance (FedRAMP/regulated env.).
• Ability to support Tier 2/3 issues, debug logs, resolve platform access issues, and maintain stability in production environments.
• Familiarity building and managing Tableau Cloud environments.
• Experience integrating ArcGIS or geospatial data systems with cloud data platforms.
• Knowledge of scripting (Python, Bash) and automation (serverless, CI/CD pipelines).
• Exposure to GKE, AKS, Docker, and microservices architectures.
• Knowledge of data mesh, ETL/ELT architectures, API integrations, and enterprise data standards.
• Strong analytical thinking to assess platform issues, make timely architectural decisions, and drive resolution in high-pressure environments.
• Ability to take end-to-end ownership of platform stability, reliability, and delivery, proactively identifying risks and driving outcomes.
• Ability to clearly translate complex technical concepts into business-friendly language and actively engage with stakeholders, leadership, and end users.
• Proven ability to lead and coordinate across engineering, data, infrastructure, and business teams, ensuring alignment and delivery of platform initiatives.

Qualifications

• Minimum 8 years of experience in multi-cloud platform expertise (Azure + GCP).
• Minimum 8 years of experience in GenAI & Enterprise AI Platform Knowledge (Gemini, Vertex AI).
• Minimum 8 years of experience in Azure Monitor, Log Analytics, GCP Cloud Monitoring, and logging frameworks to track performance, reliability, and usage.
• Minimum 8 years of experience using Logstash for log ingestion, transformation, and integration with Azure Log Analytics for proactive monitoring and alerting.
• Minimum 8 years of hands-on experience supporting data pipelines, data platforms, and analytics workloads in enterprise environments.
• Minimum 8 years of experience with Informatica Cloud (IICS), Secure Agents, APIs, and integration patterns, including handling monitoring and integration challenges.
• Minimum 8 years of strong implementation of IAM (least privilege), network security, audit logging, and compliance (FedRAMP/regulated env.).
• Minimum 3 years of familiarity building and managing Tableau Cloud environments.
• Minimum 3 years of experience integrating ArcGIS or geospatial data systems with cloud data platforms.
• Minimum 3 years of knowledge of scripting (Python, Bash) and automation (serverless, CI/CD pipelines).
• Minimum 3 years of exposure to GKE, AKS, Docker, and microservices architectures.
• Minimum 3 years of knowledge of data mesh, ETL/ELT architectures, API integrations, and enterprise data standards.
• Minimum 3 years of strong analytical thinking to assess platform issues, make timely architectural decisions, and drive resolution in high-pressure environments.
• Minimum 3 years of ability to take end-to-end ownership of platform stability, reliability, and delivery, proactively identifying risks and driving outcomes.
• Minimum 2 years of ability to clearly translate complex technical concepts into business-friendly language and actively engage with stakeholders, leadership, and end users.
• Minimum 2 years of proven ability to lead and coordinate across engineering, data, infrastructure, and business teams, ensuring alignment and delivery of platform initiatives.

Skills

• Multi‑Cloud Platform Expertise (Azure + GCP).
• GenAI & Enterprise AI Platform Knowledge (Gemini, Vertex AI).
• Azure Monitor, Log Analytics, GCP Cloud Monitoring, and logging frameworks.
• Logstash for log ingestion, transformation, and integration with Azure Log Analytics.
• Informatica Cloud (IICS), Secure Agents, APIs, and integration patterns.
• Tableau Cloud environments.
• ArcGIS or geospatial data systems with cloud data platforms.
• Scripting (Python, Bash) and automation (serverless, CI/CD pipelines).
• GKE, AKS, Docker, and microservices architectures.
• Data mesh, ETL/ELT architectures, API integrations, and enterprise data standards.
• Strong analytical thinking.
• End-to-end ownership of platform stability, reliability, and delivery.
• Clear translation of complex technical concepts into business-friendly language.
• Leadership and coordination across engineering, data, infrastructure, and business teams.

Benefits

• Equal Opportunity Employer.

Pay

TBD

Schedule

TBD