Sepal AI builds the world’s hardest tests for AI grounded in real-world software systems. We’re hiring a Data Engineer with 3+ years of experience and a strong systems mindset to help us build evaluation environments for AI in high-throughput log analysis contexts.
🧠 What You’ll Do
- Design and implement analytical schemas and pipelines using tools like BigQuery, ClickHouse, Snowflake, Redshift, and other high-performance columnar databases.
- Work on complex, distributed queries over massive log and telemetry datasets.
- Create and manage synthetic datasets that simulate real-world DevOps, observability, or cloud infrastructure logs.
- Tune and optimize distributed query execution plans to avoid timeouts and reduce over-scanning.
✅ Who You Are
- 3+ years of experience in data engineering or backend systems roles.
- Deep expertise in analytical databases and OLAP engines with a focus on large-scale query optimization, schema design, and performance tuning.
- Hands-on with log ingestion pipelines (e.g., FluentBit, Logstash, Vector) and schema design for observability systems.
- Strong SQL skills: you know how to reason through performance problems and spot inefficient query patterns.
- Bonus: Experience with Python, Docker, or synthetic data generation.
💸 Pay
$50 - 85/hr depending on experience
Remote, flexible hours
Project timeline: 5-6 weeks
