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Common Data Engineer title with broad SQL/AWS/Python requirements increases applicant density.
Data engineering skills (SQL, ETL, AWS, Python) are highly transferable across industries.
Moderate due to specific mandatory tech stack (Redshift, AWS Glue, Python) but no explicit years requirement.
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Write and optimize SQL queries for large-scale data processing using Redshift, PostgreSQL, and MySQL.
Own end-to-end delivery of change requests including requirement analysis, design, development, and implementation with full accountability.
Use AWS services (Glue, S3) for ETL processes and data warehousing, and resolve technical/operational data issues through investigations.
Strong proficiency in SQL with experience on Redshift, PostgreSQL, and MySQL databases.
Hands-on experience with ETL processes and AWS Glue and S3 services.
Programming experience in Python sufficient to develop small to medium web applications.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced with disciplined development methodologies producing scalable and maintainable data solutions.
Comfortable solving complex business problems through data processing and automation in cloud environments.
Capable of independently owning and delivering full lifecycle data engineering tasks from analysis to deployment with accountability.