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AI-Augmented Data Engineer P2 Data, Integration & Supplier Integrity

AI-Augmented Data Engineer P2 Data, Integration & Supplier Integrity

papigen
4-6 Years
Not Disclosed
  • Posted 10 hours ago
  • Be among the first 10 applicants

Job Description

Role Overview

The AI-Augmented Data Engineer will build and maintain data pipelines, integrations, data-quality rules, and curated datasets that support business journeys, dashboards, and AI-enabled features.

The candidate must have hands-on data engineering experience and at least 1 year of AI-assisted delivery experience, using AI tools to generate and test SQL, pipeline code, and data-quality checks, followed by independent review and validation.

Key Responsibilities

  • Build, maintain, and optimize ETL/ELT pipelines and data integrations.
  • Develop SQL queries, Python scripts, and data transformation logic.
  • Implement data-quality checks, source-to-target reconciliation, and exception handling.
  • Prepare curated, reliable datasets for J5 journeys and P3 AI Document Intelligence.
  • Integrate data from enterprise systems, APIs, and other sources.
  • Use AI tools to generate SQL, pipeline code, and automated tests, then review and correct the output.
  • Validate pipeline results against source data and investigate discrepancies.
  • Perform performance checks and support production troubleshooting.

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 or ETL/ELT processes.
  • Strong SQL skills, including joins, aggregations, transformations, and data validation.
  • 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.
  • Experience using AI tools to generate or improve SQL/pipeline code and tests, followed by self-review.
  • Knowledge of data-quality testing, reconciliation, and source-to-target validation.
  • Ability to identify incorrect AI-generated logic and validate data accuracy before release.

Preferred Skills

  • Databricks or Azure data services.
  • Experience with enterprise or public-sector data platforms.
  • OutSystems integrations.
  • Claude, Codex, GitHub Copilot, Databricks Assistant, or OutSystems Mentor.
  • Experience preparing curated datasets for dashboards, business applications, or AI solutions.

Skills: ai,azure data services,sql,python scripts,outsystems integrations,p2 data,databricks

More Info

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Key Skills

AI tools

OutSystems integrations

Azure data services

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