Data Engineering Testing:
Minimum 9+ years of hands-on experience as Quality Assurance Engineer
5+ years of experience in QA automation for data engineering, ETL, or similar domains.
Experience with data testing tools and frameworks such as Great Expectations or similar.
Strong expertise in Python for test automation, with experience in libraries like PyTest or unittest.
Proficiency in SQL for data validation and querying.
Hands-on experience with testing large-scale data pipelines in data platforms like Azure Databricks (preferred) or Snowflake
Azure Ecosystem Expertise:
Experience with Azure Data Cloud - ADF, Synapse, ADLS Gen 2, CosmosDB
Familiarity with Azure Event Hub or Kafka for validating streaming data pipelines.
Understanding of Azure Blob Storage and Azure Data Lake for data validation tasks.
Exposure to monitoring tools like Azure Monitor and Azure Log Analytics for analyzing test results and pipeline performance.
Familiarity with data security and governance practices for Azure Databricks
Familiarity with modern data lakehouse data formats - delta table, parquet
Knowledge of data modeling concepts such as Star Schema, Data Vault and Medallion Architecture
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