Job Summary
| Role Summary: | ||||||||||||||
| Design, develop, and implement AI-powered automation solutions that streamline data governance, discovery, retention, compliance, and operational processes across enterprise data platforms. | ||||||||||||||
| Positions | 2 | |||||||||||||
| Key Responsibilities: | ||||||||||||||
| Develop and deploy AI/GenAI and automation solutions to improve data management and governance processes. | ||||||||||||||
| Build automated workflows for data discovery, classification, metadata enrichment, retention, archival, and deletion activities. | ||||||||||||||
| Integrate AI services, APIs, and cloud-native tools into enterprise data platforms. | ||||||||||||||
| Support the development of monitoring, audit, and compliance controls within automated solutions. | ||||||||||||||
| Collaborate with architects, data engineers, governance teams, and business stakeholders to deliver scalable automation capabilities. | ||||||||||||||
| Contribute to AI model testing, deployment, and continuous improvement initiatives. | ||||||||||||||
| Key Skills: | ||||||||||||||
| AI/GenAI and Intelligent Automation | ||||||||||||||
| Python, APIs, and Workflow Automation | ||||||||||||||
| Cloud Platforms (GCP/Azure/AWS) | ||||||||||||||
| Data Engineering and Data Governance | ||||||||||||||
| Metadata Management and Data Quality | ||||||||||||||
| Monitoring, Logging, and Operational Support | ||||||||||||||
| Experience: | ||||||||||||||
| 3+ years of experience in Data Engineering, Automation, AI/ML, or software development, with hands-on experience building enterprise automation solutions. | ||||||||||||||
Key Responsibilities
| Role Summary: | ||||||||||||||
| Design, develop, and implement AI-powered automation solutions that streamline data governance, discovery, retention, compliance, and operational processes across enterprise data platforms. | ||||||||||||||
| Positions | 2 | |||||||||||||
| Key Responsibilities: | ||||||||||||||
| Develop and deploy AI/GenAI and automation solutions to improve data management and governance processes. | ||||||||||||||
| Build automated workflows for data discovery, classification, metadata enrichment, retention, archival, and deletion activities. | ||||||||||||||
| Integrate AI services, APIs, and cloud-native tools into enterprise data platforms. | ||||||||||||||
| Support the development of monitoring, audit, and compliance controls within automated solutions. | ||||||||||||||
| Collaborate with architects, data engineers, governance teams, and business stakeholders to deliver scalable automation capabilities. | ||||||||||||||
| Contribute to AI model testing, deployment, and continuous improvement initiatives. | ||||||||||||||
| Key Skills: | ||||||||||||||
| AI/GenAI and Intelligent Automation | ||||||||||||||
| Python, APIs, and Workflow Automation | ||||||||||||||
| Cloud Platforms (GCP/Azure/AWS) | ||||||||||||||
| Data Engineering and Data Governance | ||||||||||||||
| Metadata Management and Data Quality | ||||||||||||||
| Monitoring, Logging, and Operational Support | ||||||||||||||
| Experience: | ||||||||||||||
| 3+ years of experience in Data Engineering, Automation, AI/ML, or software development, with hands-on experience building enterprise automation solutions. | ||||||||||||||