AI-Augmented Data Engineer – P2 Dat...

Role Overview

The AI-Augmented Data Engineer will build and maintain robust data pipelines, integrations, data-quality rules, and curated datasets that support critical business journeys, dashboards, and AI-enabled features. The ideal candidate must possess hands-on data engineering experience combined with at least 1 year of AI-assisted delivery experience.

Key Responsibilities

• Build, maintain, and optimize ETL/ELT pipelines and complex data integrations.
• Develop advanced SQL queries, Python scripts, and sophisticated data transformation logic.
• Implement rigorous data-quality checks, source-to-target reconciliation, and exception handling protocols.
• Prepare curated, reliable datasets specifically for J5 journeys and P3 AI Document Intelligence initiatives.
• Integrate diverse data from enterprise systems, APIs, and various external sources using modern tools including OutSystems.
• Leverage AI tools (e.g., Claude, Codex, GitHub Copilot) to generate SQL/pipeline code and automated tests, followed by independent review and correction of the output.
• Validate pipeline results against source data to investigate discrepancies immediately.
• Perform performance checks and support production troubleshooting for critical systems.

Mandatory Skills & Experience

• 4+ years of overall experience in Data Engineering or a closely related technical role.
• Hands-on experience developing and maintaining data pipelines, ETL/ELT processes using Databricks/Azure services.
• Strong SQL skills including complex joins, aggregations, transformations, and validation logic.
• Proficiency in Python scripting for data processing and pipeline development.
• At least 1 year of hands-on AI-assisted delivery with concrete results from a real project (using tools like GitHub Copilot or Databricks Assistant).
• Demonstrated ability to identify incorrect AI-generated logic and validate data accuracy before release.