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Mid-level data role, metro location, and broad cloud plus Snowflake/ETL skill requirements increase applicant competition.
Core data engineering skills are transferable across industries but require cloud and Snowflake-specific experience.
Explicit 5–8 years and required Snowflake/AWS/ETL tools enforce strict shortlisting filters.
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Design, build, and maintain scalable ETL/ELT data pipelines and data platforms primarily on Snowflake and AWS.
Ensure data quality, governance, monitoring, and optimize performance for analytics, BI, and AI use cases.
Translate business data requirements into production-grade, efficient data solutions supporting advanced analytics and AI/ML pipelines.
5–8 years of hands-on experience in data engineering or data platform development.
Proficiency in SQL, Python and ETL/ELT tools like Matillion, Airflow, or dbt.
Experience with Snowflake and cloud-based enterprise data platforms, especially AWS.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related technical field.
Demonstrated ability to independently design and optimize complex data pipelines and data models at enterprise scale.
Experience bridging business requirements with technical implementation to deliver high-quality data products for BI and AI.
Strong background in managing data governance, security, and performance optimization in cloud data environments.