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Tier-1 brand, popular mid-level data engineer title, metro location and broad Snowflake/AWS skills increase competition.
Strong Snowflake and AWS specialization increases domain bias, though core data engineering skills remain transferable.
Many mandatory, platform-specific skills (Snowflake, Snowpipe, AWS, DBT, Airflow, SQL) create strict filtering.
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Design and build scalable data pipelines and data warehouse platforms using Snowflake and AWS.
Implement ELT/ETL frameworks and optimize Snowflake performance and query execution.
Integrate AWS services with Snowflake environments and support data governance and platform reliability.
Strong experience with Snowflake and AWS platforms.
Expertise in SQL Data Warehousing and ELT/ETL concepts, including Snowpipe, Streams, Tasks, and Data Sharing.
Work Experience Required: Not explicitly mentioned in the JD.
Preferably hold AWS and Snowflake certifications; knowledge of Python, DBT, Airflow, and data modeling.
Experienced in designing cloud-native scalable data solutions primarily on Snowflake and AWS.
Comfortable working with data integration, optimization, and cloud security tools such as AWS Firewall Manager.
Familiar with building robust data engineering platforms with a strong focus on performance and governance.