Data Engineer

We are looking for a passionate engineer to come collaborate and grow alongside our experienced data engineering team. The team is responsible for a broad range of systems and technologies:

• Design, build, and operate complex workflows using Apache Airflow
• Design, build, and operate data transformation pipelines in Snowflake and dbt
• Design, build, and manage distributed data science inference systems across multi-cloud environments, including AWS and GCP (and more).

• Bachelor’s or Master’s degree in an engineering discipline (BEng/MEng)
• 1-2 years of experience in a technical field
• Competency in Python and SQL
• Knowledge of systems engineering principles and product lifecycle management
• Strong communication and collaboration skills

• Flexible PTO
• Medical, dental, and vision insurance with FSA options
• Company-paid life insurance
• Paid parental leave
• 401(k) with company match
• Professional development opportunities
• 10+ paid holidays off
• Summer Fridays (we leave early)
• In-office, hybrid, and fully-remote work options available
• In-office lunches and lots of free food
• Optional in-person and virtual events (we like to celebrate!)

Compensation (for US based employees):

The anticipated salary for this position is between $100,000 and $130,000. Within the range, individual pay is determined by factors such as job-related skills, experience, and relevant education or training. If your compensation expectations fall outside of this range, it may still be worth having a conversation.

Zefr is the leader in AI-powered content classifications for brands and advertisers. Zefr’s platform is purpose built for multi-modal content understanding on open platforms like YouTube, TikTok, Meta and Snap, with pre-bid activation and verification solutions. Our products safeguard media and AI investments, while maximizing performance and efficacy on those channels.

Headquartered in Los Angeles with global offices across New York, Chicago, London, Toronto, Singapore, and more, Zefr is redefining what trust and transparency means for social media in the age of AI.