Join Sepal AI and help us create groundbreaking evaluations for AI systems utilizing real-world software data! We are on the lookout for a talented Data Engineer with a minimum of 3 years of experience and a robust systems mindset to assist in developing assessment environments tailored for AI within dynamic log analysis contexts. Your Responsibilities: Design and implement analytical schemas and pipelines using high-performance tools such as BigQuery, ClickHouse, Snowflake, Redshift, and other columnar databases. Handle complex, distributed queries over extensive log and telemetry datasets. Create and manage synthetic datasets that replicate real-world DevOps, observability, or cloud infrastructure logs. Tune and optimize distributed query execution plans to avoid timeouts and reduce over-scanning. Your Qualifications: 3+ years of experience in data engineering or backend systems roles. In-depth expertise in analytical databases and OLAP engines, specifically in large-scale query optimization, schema design, and performance enhancement. Proficient in log ingestion pipelines such as FluentBit, Logstash, or Vector, with strong schema design skills for observability systems. Exceptional SQL skills to analyze performance issues and rectify inefficient query patterns. Bonus: Familiarity with Python, Docker, or synthetic data generation. Pay: $50 - 85/hr based on experience Remote, flexible hours Project timeline: 5-6 weeks