Robust experience in ETL testing and data warehouse concepts. • Hands-on expertise in Databricks (including notebooks, clusters, and jobs). • Proficiency in SQL for data validation and analysis. • Experience with big data technologies (Spark, PySpark, Delta Lake). • Familiarity with cloud platforms (Azure, AWS, or GCP) and their data services. • Knowledge of data modeling, data quality frameworks, and BI tools. • Strong analytical and problem-solving skills. • Excellent communication and documentation abilities.
ETL / Data Warehouse Testing: o Strong experience in DWH concepts (Facts, Dimensions, Star/Snowflake schema) o Hands-on data validation across large datasets • Databricks: o Experience validating data pipelines built on Databricks o Working knowledge of notebooks and Delta Lake concepts • SQL: o Strong proficiency in writing complex SQL queries (joins, subqueries, aggregations, window functions)
- Ability to perform large-volume data validation and reconciliation • Python (Basic to Intermediate): o Ability to read/write simple Python scripts for data validation, automation support, or log analysis