Clara IT Systems
Data AI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data AI Engineer with a contract length of "unknown," offering a pay rate of "unknown." Key skills include Databricks Lakehouse, SQL, AI/ML model development, and strong Python/PySpark expertise. Experience in data governance and Azure integration is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 8, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#PySpark #Spark SQL #BI (Business Intelligence) #Deployment #Anomaly Detection #AI (Artificial Intelligence) #Azure #Automation #Data Governance #MLflow #Data Engineering #Spark (Apache Spark) #Databricks #Data Quality #SQL (Structured Query Language) #ML (Machine Learning) #Python
Role description
Please see the required skillset for the AI Engineer (Databricks) role. This role is aligned to the AI & Automation Enablement workstream, including autonomous AI agents, data quality AI, decision intelligence, advanced analytics, ML/AI, Databricks SQL, Unity Catalog, Databricks Lakehouse, AI/BI Genie, and Agent Bricks capabilities.
Required Skillsets: AI Engineer (Databricks)
• Databricks Lakehouse architecture and implementation
• Databricks SQL, notebooks, workflows, and job orchestration
• AI/BI Genie implementation and business-facing conversational analytics
• Agent Bricks and autonomous AI agent development within Databricks
• MLflow for model tracking, deployment, and lifecycle management
• AI/ML model development, validation, and operationalization
• GenAI and AI agent development using Databricks capabilities
• Data quality automation, anomaly detection, and intelligent validation
• Unity Catalog, data governance, lineage, and access control
• Integration with Azure, APIs, and enterprise data sources
• Experience building AI-driven recommendations, smart notifications, and decision intelligence workflows
• Strong Python, PySpark, SQL, and data engineering fundamentals
Please see the required skillset for the AI Engineer (Databricks) role. This role is aligned to the AI & Automation Enablement workstream, including autonomous AI agents, data quality AI, decision intelligence, advanced analytics, ML/AI, Databricks SQL, Unity Catalog, Databricks Lakehouse, AI/BI Genie, and Agent Bricks capabilities.
Required Skillsets: AI Engineer (Databricks)
• Databricks Lakehouse architecture and implementation
• Databricks SQL, notebooks, workflows, and job orchestration
• AI/BI Genie implementation and business-facing conversational analytics
• Agent Bricks and autonomous AI agent development within Databricks
• MLflow for model tracking, deployment, and lifecycle management
• AI/ML model development, validation, and operationalization
• GenAI and AI agent development using Databricks capabilities
• Data quality automation, anomaly detection, and intelligent validation
• Unity Catalog, data governance, lineage, and access control
• Integration with Azure, APIs, and enterprise data sources
• Experience building AI-driven recommendations, smart notifications, and decision intelligence workflows
• Strong Python, PySpark, SQL, and data engineering fundamentals
