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

Papigen; India; On-site; INR 1,200,000 - 2,100,000; Full time

Job summary

Papigen seeks an AI-Augmented Data Engineer to build and maintain data pipelines, integrations, and data-quality rules that power dashboards and AI-enabled features.

The role requires 4+ years in data engineering, plus at least 1 year of AI-assisted delivery, with hands-on SQL and Python, and the ability to validate AI-generated outputs before release. Based in India, this full-time position focuses on reliable, scalable data platforms.

Qualifications

• 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.

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.

Skills

SQL

Python

ETL/ELT pipelines

AI-assisted delivery

Data quality testing

Data reconciliation

Source-to-target validation

Databricks

APIs integration

Tools

Databricks

Azure data services

OutSystems integrations

Job description

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