Build and scale data pipelines to process millions of user votes for AI model evaluation. Partner with researchers to deliver insights via dashboards, ensuring data quality and reliability in a fast-paced environment. Requires 5+ years in data engineering with big data tools.
Salary not listed
Hybrid5+ YOEData Engineering
About the role
Responsibilities
Design and build robust data pipelines to ingest, process, and transform user vote data to features essential for model performance evaluation.
Collaborate with researchers and product leadership to understand product goals and necessary data.
Design and implement solutions to generate result dashboards and reports, providing useful information for the public, model providers, and researchers.
Ensure the integrity, data quality, and reliability of the pipelines.
Scale our data infrastructure to accommodate increasing data volumes and evolving analytical needs.
Requirements
5+ years of experience in software engineering, with a dedicated focus on data engineering and big data technologies.
Proficiency in SQL and at least one programming language commonly used for data analysis (Python (preferred), Scala, R).
Hands-on experience with data processing and pipeline frameworks (Apache Spark, Ray Data, etc.) and at least one popular big data analytics platform (Databricks, Snowflake).
Demonstrated experience in designing, implementing, optimizing, and debugging production data pipelines.
Preferred Qualifications
Prior work in data analytics or datalake platforms.
Experience in advanced data analysis tools, such as Delta Lake, streaming tables.
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