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Common mid-level Data Engineer role with metro/hybrid location and broad AWS/Snowflake skillset increases candidate competition.
Data engineering skills (AWS, Snowflake, Python) are highly transferable across industries.
Explicit 2–4 years plus mandatory AWS, Snowflake, Python, and CI/CD requirements tighten screening.
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Deliver complex data engineering solutions using AWS and Snowflake technologies, ensuring code quality and adherence to data protection standards.
Mentor junior engineers and contribute to team capability development and technical standards.
Influence architecture decisions, quality practices, and participate in organization-level cloud initiatives.
2 to 4 years of experience as a Data Engineer with a proven track record.
Bachelor’s or Master’s degree in Computer Science or related field.
Proficiency with AWS services including S3, Lambda, SNS, EC2, IAM, KMS and Snowflake features such as streams, tasks, stored procedures, snowpipe, and data sharing.
Experience with Python, SQL, relational databases, CI/CD pipelines in GitHub and Jenkins.
Experienced in building and optimizing data pipelines within AWS and Snowflake environments.
Capable of independently delivering tasks with maintainable code while following established coding standards and security practices.
Adaptable between independent and collaborative work, with a mindset for AI adoption to improve productivity and operational efficiency.