Principal Data Engineer
Principal Data Engineer is an open role at Serhant, a company in media, entertainment and advertising. The role is remote, and the posting gives United States as the location. We classify it under data and machine learning. Technologies named in the posting: ClickHouse, PostgreSQL, Azure, Airflow, dbt and Kafka. It asks for 5+ years of experience. Visa sponsorship is not offered. Serhant has 6 open positions on this site, 1 of them in IT and engineering.
Posted today · Last checked 2026-10-22
About Serhant
Media, entertainment and advertising Non-tech company with an IT team 6 open positions, 17% in IT and engineering. Most open roles: Creative, media and writing (2), Data and machine learning (1), Finance and legal (1).
Similar jobs
1,048 open data and machine learning jobs in the United States · 714 open remote data and machine learning jobs
- Data Engineer — Accenture Federal Services, Arlington, VA
- Staff Data Scientist, Marketing Analytics — Chime Financial, Inc, San Francisco, CA, USA
- Machine Learning Engineer, Scenes — Waymo, Mountain View, California, United States, San Francisco, California, United States
- Senior Software Engineer - Computer Vision — Verkada, San Mateo, CA United States
- Machine Learning Engineer III, Shield — Box, Redwood City, CA
- Data Analyst, Operations — Rocket Money, San Francisco, CA, Washington, D.C., New York City, N.Y., Detroit, MI, Phoenix, AZ, Miami, FL, Denver, CO., Remote (USA)
- Staff Machine Learning Engineer, Recommendation Systems - Quora (Remote) — Quora, Remote - Multiple Locations | United States | Ireland | Canada | & 13 other countries
- Forward Deployed AI Engineer — Talkdesk, United States Remote
| Workplace | Remote |
| Seniority | Staff |
| Role | Data and machine learning |
| Countries | United States |
| Languages | PythonSQLTypeScript |
| Key facts | Stack: Python, SQL, TypeScript, ClickHouse, PostgreSQL, Azure, Airflow, dbt, Kafka, Flink, Spark, LLM · Experience: 5+ years · Remote · Visa sponsorship: no |
The full description is on the original posting. Labels are set automatically and can be wrong. About the data