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Strong brand and metro location but senior, specialized data role reduces applicant density.
Medium - core data engineering skills transferable, but Snowflake, vector DB and LLM integration increase specificity.
High - 8+ years plus mandatory Snowflake, AWS, Python, and graph/vector database skills.
Design, develop, and maintain scalable AWS data pipelines using services like S3, Glue, Lambda, Redshift, and EMR.
Build and optimize data warehousing on Snowflake including performance tuning and data modeling.
Integrate graph and vector databases with LLM-based AI workflows and ensure data quality, pipeline performance, and security.
Minimum 8+ years of experience in data engineering or related roles.
Strong hands-on experience with AWS cloud services and Snowflake data warehousing.
Proficiency in Python and SQL for data transformation and pipeline development.
Onsite work required 5 days a week; Bachelor's or Master's degree in Computer Science, Engineering, or related field.
Experienced in building data pipelines in cloud environments with advanced Snowflake expertise.
Skilled in working with graph databases (e.g., Neo4j) and vector databases (e.g., Milvus) integrating with AI/LLM applications.
Comfortable collaborating across cross-functional teams in Agile environments using tools like Git and Azure DevOps.