A rapidly scaling tech company is building out its Data Engineering team to support a high-volume, real-time data platform.

The system processes tens of billions of events daily and powers reporting, optimization, and core business operations under strict SLA requirements. The environment is highly distributed, with a strong focus on scalability, performance, and modern data infrastructure.

Responsibilities

• Design and build scalable distributed data pipelines
• Optimize performance across streaming and batch systems
• Ensure data quality and reliability across multiple sources
• Partner with analytics and engineering teams to deliver usable datasets
• Contribute to architectural decisions and mentor team members

Tech Environment

Python, Spark, Kafka, Presto/Trino, Airflow, Kubernetes, Hive, SQL, Iceberg, and cloud-based analytics tools

Background

• 8+ years in data engineering
• Strong Python and SQL skills
• Experience with Spark and distributed systems
• Familiarity with on-prem and/or cloud environments

Fully remote (U.S. hours). Interview process includes a coding assessment and technical evaluation.