At Vega IT, I built and maintained Azure Data Factory and Databricks pipelines that supplied production data for customer analytics and reporting.
I investigated data inconsistencies, validated outputs, and traced issues from source systems through transformations to downstream reports. I also defined validation rules for a Databricks DQX proof of concept and identified quality issues across datasets.
For customer intelligence and NPS analysis, I prepared datasets and used SQL and Python to compare expected and actual results and support root-cause analysis.
Earlier, as a Data Engineer Intern at Vega IT, I designed a star-schema data model and automated ETL workflows with Python and Apache Airflow. I also integrated API data sources, implemented Kafka-based streaming, and created an interactive Power BI dashboard.
