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Senior Data Engineer

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đŸ”„ 0 minutes ago

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Posted on SurveyMonkey's careers page, not through a job board

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SurveyMonkey

1001 - 5000 employees

☁ SaaS

đŸ€ B2B

SaaS ‱ B2B

SurveyMonkey is an online survey and forms platform that lets organizations and individuals build, send, and analyze surveys to collect feedback and insights. The platform offers 500+ templates, AI-assisted survey creation, a global audience panel of 335M+ respondents, analytics and integrations, and enterprise-grade features for secure, large-scale survey programs. It’s used across customer experience, employee feedback, market research, event registration, and more; the company markets itself as a continuous insights/SaaS platform serving 260K+ organizations worldwide.

📋 Description

‱ Build new data models, including Fact and Dimension models ‱ Write performant and idempotent transformations in Snowflake ‱ Build data pipelines using modular Python scripts ‱ Write well-tested, production-ready Python and Snowflake SQL code ‱ Implement ETL/ELT best practices ‱ Translate business requirements into technical specifications, define project scope, and deliver deployable code ‱ Write complex Snowflake SQL jobs and sophisticated queries across datasets ‱ Document systems for internal and external stakeholders ‱ Monitor and debug data pipelines running on Airflow ‱ Participate in code reviews ‱ Mentor data engineers on best practices and coding standards

🎯 Requirements

‱ Experience building data models (Fact vs Dimension) ‱ Experience writing performant and idempotent transformations in Snowflake ‱ Experience building data pipelines using Python scripts in a modular/loop context ‱ Production-ready Python and Snowflake SQL coding skills ‱ Hands-on experience implementing ETL or ELT best practices ‱ Ability to translate business requirements into technical specifications, define project scope, and deliver deployable code ‱ Experience writing complex Snowflake SQL jobs and sophisticated queries across entire datasets ‱ Experience documenting systems for internal and external stakeholders ‱ Experience monitoring and debugging Airflow data pipelines ‱ Experience participating in code reviews ‱ Experience mentoring data engineers on best practices and coding standards ‱ Ability to work 40 hours per week ‱ Must reside in an eligible U.S. location and be legally authorized to work in the United States

đŸ–ïž Benefits

‱ Telecommuting permitted ‱ Flexible, hybrid work environment ‱ CHOICE Fund programs to help employees thrive in work and life ‱ Career growth opportunities ‱ Inclusive workplace and equal employment opportunity ‱ Disability accommodations available

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