👋 Hero Section

Hi, I’m Ervisa Beinto – Senior Data Analyst (Hybrid Analytics - Data Engineering Role)

I design and deliver data solutions that turn complex pipelines into clear business insights, bridging analytics, engineering, and strategy.

📌 About Me

I describe myself as a T-shaped professional: I go deep in analytics and data engineering, while maintaining a broad understanding of business, reporting, and cross-functional collaboration. This blend has helped me lead successful migrations, optimize pipelines, and translate data into measurable business impact.

💼 Case Studies

🔹 Case Study: Migration from Azure Data Factory to Databricks with Airflow

Challenge

The company relied on Azure Data Factory pipelines and embedded SQL in 100+ Power BI reports, which created major challenges:

• No clear structure for fact/dimension tables and dependencies.
• 400+ SQL queries needed to be migrated and restructured.
• Power BI reports contained embedded SQL that had to be redesigned for Databricks.
• Difficulties managing Airflow DAG dependencies, especially when fact tables depended on other facts.
• Lack of automated QA to ensure migrated data matched the old environment.

Solution

I designed and led the migration to a medallion architecture (bronze → silver → gold) in Databricks, orchestrated with Airflow. My key contributions:

• Automated Dependency Detection
  • Built a Python script to parse SQL/YAML and automatically detect table dependencies.
  • Used this to generate DAGs dynamically and ensure correct orchestration in Airflow.
• Databricks Integration
  • Connected Airflow DAGs directly to Databricks jobs using the REST API.
  • Created utility scripts to fetch and map Databricks job IDs, ensuring smooth deployment.
  • Used asset bundles + Jinja templates to standardize job deployment.