AI Data Engineer (Hybrid)

Responsibilities

• Design and develop AI-enabled analytics solutions supporting enterprise reporting, forecasting, operational insights, and intelligent decision-making.
• Support enterprise AI initiatives including: Generative AI integrations, AI-assisted analytics, Natural language reporting, Predictive analytics, Recommendation and insight generation capabilities.
• Develop reusable analytics frameworks and scalable data products supporting enterprise reporting and AI use cases.
• Identify opportunities to leverage AI capabilities to improve reporting development efficiency and business insight generation.
• AI-Driven Data Quality & Automation
• Design and implement AI-driven solutions that proactively identify: data anomalies, schema changes, integration failures, reporting inconsistencies, and data quality issues across enterprise platforms.
• Develop intelligent monitoring and alerting frameworks that detect abnormal data patterns, missing data, volume fluctuations, and KPI deviations before impacting business operations.
• Build AI-assisted development accelerators that reduce analytics and reporting development time through: automated code generation, reusable semantic modeling patterns, metadata-driven development, and AI-assisted testing and validation.
• Create AI-enabled solutions that proactively analyze upstream system and schema changes to identify potential downstream reporting and integration impacts.
• Implement machine learning and AI techniques to improve: data validation, matching accuracy, duplicate detection, and automated remediation workflows.
• Implement automated data profiling and data lineage solutions that improve governance, transparency, and operational stability.
• Leverage AI capabilities to streamline: report development, semantic model generation, SQL optimization, documentation, and operational support processes.
• Collaborate with governance and architecture teams to establish standards for responsible AI usage within analytics and reporting ecosystems.
• Evaluate emerging AI technologies and platforms to improve enterprise analytics capabilities, development efficiency, and business insight generation.

Qualifications

• Bachelor's degree in Computer Science or related field
• 5+ years related experience