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Mid-level generalist data engineer in metro with common title and experience range increases applicant competition.
Snowflake, ETL and AWS skills are broadly applicable across industries, enabling transferable candidacies.
Explicit 3-5 years plus required Snowflake, ETL and AWS skills raise hiring filter rigidity.
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Build and manage ETL pipelines leveraging Snowflake and AWS services such as S3, Glue, and Lambda.
Perform data analysis to support data processing and integration workflows.
Utilize Control-M and Jenkins for workflow scheduling and CI/CD pipeline management.
3 to 5 years of professional experience in software engineering or relevant data engineering roles.
Proficiency in Snowflake for data warehousing solutions.
Hands-on experience with AWS services including S3, Glue, and Lambda.
Familiarity with ETL tools, Control-M, Jenkins, and GitHub for pipeline orchestration and version control.
Experienced in designing and implementing scalable ETL data pipelines using Snowflake and AWS ecosystem.
Capable of managing workflow automation and continuous integration/deployment in a data environment.
Comfortable working with database technologies like Postgres and data visualization tools such as Tableau.