Sr. Manager, Content Promotion & Distribution Data Engineering
Netflix
Multiple Locations
Base: $525,000.00 - $950,000.00; bonus/equity: no ...
Data engineering leadership 7+ years
Multi-modal data pipelines
Batch and streaming data processing
Netflix’s Content Promotion & Distribution Data Engineering team builds robust, scalable data foundations to power analytics, experimentation, and machine learning across global content promotion and distribution
Job Summary
Netflix’s Content Promotion & Distribution Data Engineering team builds robust, scalable data foundations to power analytics, experimentation, and machine learning across global content promotion and distribution.
The role involves hiring and leading a diverse team of data and ML engineers, partnering with cross-functional teams, and driving technical vision for multi-modal data infrastructure.
Netflix offers comprehensive benefits including health plans, mental health support, 401(k) with employer match, stock options, flexible paid time off, and a unique inclusive culture.
Matching Summary
Netflix’s Content Promotion & Distribution Data Engineering team builds robust, scalable data foundations to power analytics, experimentation, and machine learning across global content promotion and distribution.
Salary
Base: $525,000.00 - $950,000.00; Bonus/Equity: No bonuses, stock option program available; Benefits: Comprehensive health plans, 401(k) with match, paid leave, mental health support
Skills & Requirements
Must-have
Data engineering leadership 7+ years
Multi-modal data pipelines
Batch and streaming data processing
ML and experimentation-ready data products
Data modeling and warehousing
Cloud-based big data technologies
Cross-functional stakeholder collaboration
Nice-to-have
Inclusive team environment
Psychological safety focus
Career development mentoring
Strong communication skills
Impact-oriented and humble mindset
Experience with GenAI/ML use cases
Shared resource team management
Key Requirements
7+ years leading data engineering teams
Experience managing managers and heterogeneous teams
Proven track record in complex data engineering domains
Expertise in batch/streaming pipelines and data modeling