| Location | Austin, Texas |
| Minimum Requirements: Candidates that do not meet or exceed the minimum stated requirements (skills/experience) will be displayed to customers but may not be chosen for this opportunity. | |||
| Actual Years Experience | Years Experience Needed | Required/ Preferred | Skills/Experience |
| 8 | Multi‑Cloud Platform Expertise (Azure + GCP) | ||
| 8 | GenAI & Enterprise AI Platform Knowledge (Gemini, Vertex AI) | ||
| 8 | Expertise in Azure Monitor, Log Analytics, GCP Cloud Monitoring, and logging frameworks to track performance, reliability, and usage. | ||
| 8 | Experience using Logstash for log ingestion, transformation, and integration with Azure Log Analytics for proactive monitoring and alerting | ||
| 8 | Ability to design alerting solutions using Twilio (SMS/voice) for ETL failures and operational notifications. | ||
| 8 | Experience with Blob Storage, Data Lakes, and structured storage systems enabling analytics and AI workloads. | ||
| 8 | Hands-on experience supporting data pipelines, data platforms, and analytics workloads in enterprise environments | ||
| 8 | Experience with Informatica Cloud (IICS), Secure Agents, APIs, and integration patterns, including handling monitoring and integration challenges. | ||
| 8 | Strong implementation of IAM (least privilege), network security, audit logging, and compliance (FedRAMP/regulated env.). | ||
| 8 | Ability to support Tier 2/3 issues, debug logs, resolve platform access issues, and maintain stability in production environments | ||
| 3 | Preferred | Familiarity building and managing Tableau Cloud environments | |
| 3 | Preferred | Experience integrating ArcGIS or geospatial data systems with cloud data platforms. | |
| 3 | Preferred | Knowledge of scripting (Python, Bash) and automation (serverless, CI/CD pipelines). [https://ou...essageItem | Outlook] | |
| 3 | Preferred | Exposure to GKE, AKS, Docker, and microservices architectures. | |
| 3 | Preferred | Familiarity with data mesh, ETL/ELT architectures, API integrations, and enterprise data standards. | |
| 3 | Preferred | Strong analytical thinking to assess platform issues, make timely architectural decisions, and drive resolution in high-pressure environments. | |
| 3 | Preferred | Ability to take end-to-end ownership of platform stability, reliability, and delivery, proactively identifying risks and driving outcomes | |
| 2 | Preferred | Ability to clearly translate complex technical concepts into business-friendly language and actively engage with stakeholders, leadership, and end users | |
| 2 | Preferred | Proven ability to lead and coordinate across engineering, data, infrastructure, and business teams, ensuring alignment and delivery of platform initiatives. | |
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