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Job Description
Structured overview of role & requirementsAbout This Role
Develop and optimize large-scale data pipelines using Snowflake, Google Cloud, and AWS to support integration, storage, and reporting needs.
Lead complex ETL processes, Python scripting including automation and generative AI prompt engineering, and validate data and AI outputs for quality and accuracy.
Mentor junior engineers, perform code reviews, troubleshoot and optimize data workflows, while staying updated on generative AI and advanced cloud data technologies.
Minimum Requirements
Bachelor’s degree in Computer Science, Data Science, Information Systems, or related field.
2-4 years of data engineering experience with advanced expertise in Snowflake, SQL, ETL, and Python including generative AI prompt engineering.
Hands-on experience with AWS services (S3, EC2, Lambda, Fargate) and familiarity with GCP data tools (BigQuery, Cloud Functions, Vertex AI).
Experience with CICD pipelines (Jenkins, Terraform, Harness, ADK), ETL tools like Informatica, and data visualization tools (ThoughtSpot).
Ideal Candidate Profile
Experienced in building and leading AI-integrated data workflows including generative AI model orchestration and output validation.
Strong technical leadership demonstrated by mentoring junior engineers and driving data quality and scalability improvements.
Operates effectively at the intersection of large-scale cloud data engineering and emerging AI technologies, especially within AWS and GCP environments.