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05 · Brussels · Full-time
Python Automation Developer & Analyst
APB (Algemene Pharmaceutische Bond)
Automated pharmaceutical data migration and reporting pipelines.
Focus areas
- Data Engineering
- DevOps
Technologies
- Python
- Apache Airflow
- PySpark
- Pandas
- MS SQL Server
- Qlik Sense
Overview
This record covers the Python Automation Developer & Analyst role at APB (Algemene Pharmaceutische Bond) in Brussels, running from October 2021 to July 2022. The work delivered automation for pharmaceutical data migration and reporting pipelines.
Architecture & Development
- Designed ETL pipelines with Apache Airflow, connecting legacy XML feeds with modern JSON/CSV integrations.
- Built distributed data processing flows with PySpark, cleansing and aggregating millions of records.
- Used Pandas for analytics transformations and integrated data outputs into MS SQL Server.
- Designed reporting dashboards in Qlik Sense to visualize KPIs and compliance metrics.
DevOps & Testing
- Automated deployment of Airflow DAGs through Git-based workflows.
- Introduced data quality validation scripts to flag anomalies before ingestion.
- Documented data lineage and process flows for regulatory audits.
Key Contributions
- Reduced manual migration workload by 60% through fully automated ETL pipelines.
- Improved reliability by implementing retry and monitoring mechanisms in Airflow DAGs.