Data Engineer
Summary
Data engineer designing and optimizing scalable distributed streaming and batch pipelines for a real-time platform processing tens of billions of events daily. Core stack is Python, SQL, Spark, Kafka, Presto/Trino, Airflow, Kubernetes, Hive, and Iceberg. Fully remote role working U.S. hours.
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.
