Senior Data Engineer (Snowflake)

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Kostenlos, nach der Anmeldung.

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Beschreibung

Requirements description Ability to work partially within the U.S. time zone (during onboarding: calls up to 10:00 PM CET a few times a week; later: up to 5/6/7 PM CET) 6+ years of experience in Data Engineering, with Snowflake as a primary data platform. Proven hands-on experience optimising Snowflake warehouses and storage for performance and cost efficiency in production environments. Experience building and optimising pipelines processing very large datasets, including full transaction-level histories rather than samples. Strong SQL and Python skills, with the ability to own data pipelines end to end. Practical experience with data quality engineering, including validation, reconciliation, monitoring, and ongoing data reliability. Nice to have Experience working with financial, market, transaction-level, or time-series data. Familiarity with accuracy and tracking metrics such as correlation and mean absolute error (MAE). Experience integrating and maintaining third-party data feeds or working with data licensing and data-sharing arrangements. Practice with dbt or similar data transformation frameworks on Snowflake. Your responsibilities Build and maintain a Snowflake-based evaluation pipeline to measure the accuracy of new datasets, both independently and combined with existing data. Implement evaluation metrics such as correlation and mean absolute error (MAE) to compare estimated company revenue against reported results. Optimise Snowflake performance and compute costs

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