Can you explain briefly what technologies you have used or what kind of work you have done on a daily basis, and what kind of data or transformations you have dealt with?
💡 Model Answer
On a daily basis I work with a stack that includes Python, JavaScript, and SQL. I build ETL pipelines using Apache Airflow to extract data from REST APIs and CSV files, transform it with Pandas and Spark, and load it into a PostgreSQL data warehouse. I also use Docker for containerization and GitHub Actions for CI/CD. The data I handle ranges from user activity logs (structured JSON) to transactional records (CSV). Transformations involve cleaning missing values, normalizing timestamps, aggregating metrics, and enriching records with geolocation data. I monitor pipeline health with Prometheus and alert on failures. This workflow ensures data quality and timely availability for downstream analytics.
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