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Linh Pham

@linhpham3

Data Engineer at Informa Markets who automated data enrichment workflows with n8n, JavaScript, and AI agents at 95–97% accuracy.

Vietnam

Message

At Informa Markets, I developed automated data enrichment pipelines using n8n, JavaScript, and AI agents to extract and standardize information from unstructured data. The workflows achieved 95–97% accuracy.

I also built and maintained regional Power BI dashboards for ASEAN events, tailoring SQL queries and visualizations to business requirements. I validated data across multiple databases using SQL.

At ATM Luxury Wigs, I designed an end-to-end ETL pipeline with Python and SQL to centralize data from fragmented sources. I also maintained Excel dashboards for executive KPI reporting.

In a project, I implemented a data lake using MongoDB integrated with BigQuery, with Python-based AWS Lambda processing. I graduated from Hoa Sen University with High Distinction as Programme Valedictorian.

Experience

Work history, roles, and key accomplishments

Data Engineer (ASEAN Team)

Informa Markets

Sep 2025 - Feb 2026 (5 months)

Developed and deployed automated data pipelines using n8n, JavaScript, and AI agents to extract and standardize complex information from unstructured raw data. Built and maintained regional Power BI dashboards for ASEAN events, tailoring SQL queries and visualizations to meet specific business requirements.

N8n JavaScript AI Agents Power Automate Power BI SQL Data Validation ETL Data Enrichment Automation

Data Management Executive

ATM Luxury Wigs

Jan 2025 - Aug 2025 (7 months)

Designed and implemented an end-to-end ETL pipeline using Python and SQL to centralize business data from fragmented sources. Maintained and enhanced recurring Excel-based executive dashboards to monitor key performance indicators and support strategic business decisions.

Python SQL ETL Excel Data Warehouse Business Intelligence Data Governance Data Analysis

Implementing a Data Lake Using MongoDB

Project

Sep 2023 - Dec 2023 (3 months)

Engineered a scalable Data Lake using MongoDB integrated with BigQuery, optimizing storage efficiency and high-speed data retrieval for analytical purposes. Developed and optimized Python-based AWS Lambda functions for real-time data processing, utilizing EventBridge for orchestration and SNS for automated alerting.