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Mid-level, generalist Data Engineer in a metro with common Azure/PySpark skills drives high competition.
Core data engineering skills are broadly transferable across industries.
Explicit 3+ years plus mandatory Azure, PySpark, and ETL skills increase shortlisting strictness.
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Build and maintain scalable data pipelines using Python/PySpark and Azure data services.
Develop ETL/ELT solutions with Azure Data Factory, Data Lake, Blob Storage, Databricks, Synapse, and Azure SQL.
Write complex SQL queries and transformations, and troubleshoot data pipeline issues following engineering best practices.
Minimum 3 years of experience in Data Engineering or Data Warehousing.
Proficient in Python/PySpark and SQL for data pipeline development.
Hands-on experience with Azure data services including Azure Data Factory, Data Lake, Blob Storage, Databricks, Synapse, and Azure SQL.
Education: Bachelor's or postgraduate degree in relevant field (B.Sc./BCA/B.Tech/B.E. or equivalent).
Experienced working with Azure cloud platform and data engineering tools (such as Azure Databricks or Spark).
Comfortable collaborating with business and technical teams to deliver data solutions.
Capable of troubleshooting and resolving complex pipeline and data issues while following engineering best practices.