Azure AI & Data Engineer

Please note before applying:
This position requires onsite work at our headquarters in South Jordan, UT. We are only considering local candidates. Thank you!

The Ultradent Data & Analytics Team is looking for a passionate and solution‑oriented Azure AI & Data Engineer to help implement data pipelines and data architecture on Azure to enhance analytical solutions, deepen understanding of business activity, influence innovation, and deliver actionable insights.

• General & Core Engineering:
  • Thought leadership in technology innovation and transformation.
  • Maintaining applications ensuring high availability, performance and user experience.
  • Creates and maintains optimal data pipeline architecture on the Azure platform. Ensures that system designs adhere to solution architecture design and are traceable to functional as well as non‑functional requirements.
  • Designs relational and non‑relational data stores on Azure. Builds analytical tools to provide actionable insights from key business performance metrics.
  • Leverages Azure Data Factory and Databricks to assemble large, complex data sets that meet end‑user and business requirements. Designs new solutions and services to improve overall user experience.
  • Identifies, designs, and implements internal process improvements such as automating manual processes and optimizing data delivery. Defines system design standards to improve and sustain standardization.
  • Expertise in Azure Dev Ops concepts and implementations, including git, CI/CD pipelines, IaC, Docker containers, and Work Items.
  • Assists Manager‑Data Administration in leading coordination with other staff to ensure data handling meets organizational objectives for data quality, business process management, and risk management.
  • Provides technical mentoring to other team members for best practices on data engineering and cloud technologies.
• Data Architecture and Governance:
  • Designs and governs data models:
    • Defines and enforces logical and physical data models for both the Azure Data Lake and the Azure Synapse Analytics data warehouse.
    • Leads the effort to standardize data definitions, metadata management, and data lineage across the Azure platform to ensure consistency and quality.
  • Architects scalable data ecosystems:
    • Develops and maintains the multi‑layered Data Lake architecture (e.g., Raw, Bronze, Silver, Gold zones) to optimize for ingestion, transformation, and consumption of data by both BI and AI initiatives.
    • Designs and implements real‑time and batch data ingestion strategies, ensuring low latency and high reliability for critical business data.
    • Evaluates and recommends new Azure services or architectural patterns to continuously improve data security, performance, and cost efficiency of the overall data ecosystem.
  • Ensures data quality and reliability:
    • Establishes and monitors data quality checks and validation rules within data pipelines to maintain a high level of trust in the datasets used for reporting and machine learning models.
    • Implements schema evolution strategies to manage changes in source data and prevent pipeline breaks.
• AI/ML and Automation:
  • Designs and implements AI/ML solutions:
    • Develops, trains, and deploys machine learning models using Azure Machine Learning (AML) / Azure AI Studio or equivalent platforms.
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    Builds end‑to‑end MLOps pipelines (e.g., model registration, automated retraining, deployment via Azure Kubernetes Service/Managed Endpoints) using Azure Dev Ops and AML.
  • Hands‑on experience implementing data and AI workflow automation using n8n, Microsoft Power Automate, or equivalent tools to connect Azure services, databases, and enterprise applications.
• AI workflow integration and automation:
  • Architects and implements low‑code/no‑code AI workflow automation using n8n or equivalent tools (e.g., Power Automate, Zapier, Apache Airflow).
  • Integrates AI services (e.g., Azure Cognitive Services, custom models) with business processes, data pipelines, and third‑party systems via REST APIs and webhooks.
  • Designs and maintains real‑time AI inference services and ensures their scalability and performance.

• Preferred Technology
  
  Experience:
  
  
  • Azure PaaS, Data analytics, Data warehousing…