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Tier-1 employer, mid-level data engineer role in metro with popular skillset and broad hiring pool.
Data engineering skills transferable but Snowflake, AWS, and vector/graph specialization increases domain specificity.
Explicit 5–8 year requirement plus mandatory Snowflake, AWS, Python, and vector/graph experience.
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Design, develop, and maintain scalable data pipelines on AWS using services like S3, Glue, Lambda, Redshift, and EMR.
Build and optimize data warehousing solutions using Snowflake, including performance tuning and data modeling.
Write efficient Python and SQL code for data transformation while ensuring data quality, reliability, and security throughout the pipelines.
5-8 years of experience in data engineering or related roles.
Strong hands-on experience with AWS cloud services and Snowflake.
Advanced proficiency in Python and SQL, with knowledge of graph and vector data modeling.
Work onsite five days a week; Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Experienced in building and optimizing scalable data pipelines and warehousing solutions in AWS environments.
Proficient with Snowflake architecture and performance tuning, plus practical use of graph and vector database technologies.
Familiar with CI/CD pipeline development (GitHub Actions) and Agile backlog management using Azure DevOps.