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Tier-1 brand, metro location, and common entry-level data skills create high candidate competition.
Role's Azure-centric ETL and data platform focus moderately reduces cross-industry transferability.
Explicit 0-1 year requirement and Azure/ETL skills create moderate shortlisting filters.
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Assist in maintaining and monitoring Azure-based data platforms including Azure Data Factory, Azure Databricks, Azure SQL Database, and Azure Synapse Analytics.
Support development and maintenance of ETL/ELT pipelines using Azure Data Factory and Databricks, including writing and optimizing SQL queries and Python scripts.
Perform data quality checks, troubleshoot data platform issues, document data flows and technical specifications.
Bachelor's degree in Computer Science, Information Technology, Computer Applications, Engineering, or related field.
0-1 year of experience in Data Engineering, Data Analytics, Cloud Technologies, or Software Development; internship experience in relevant domains preferred.
Basic understanding of Azure cloud services, SQL, and Python programming required.
Experience or familiarity with Azure Data Factory, Databricks, Azure SQL, Git version control, and knowledge of data warehousing and ETL concepts.
Early-career professional or recent graduate with internship exposure to Azure or Data Engineering.
Comfortable operating in hybrid work environments supporting cloud-based data platforms and supporting incident troubleshooting.
Able to handle technical tasks related to ETL pipeline maintenance, data quality validation, and documentation with attention to detail and collaboration.