How Do I Get A Job With Netflix

Netflix; Atlanta (GA); On-site; USD 27,552 - 41,328; Full time

Job summary

Netflix is seeking a Data Engineering Manager in Atlanta to lead a team of data engineers, researchers, and data scientists. You will define the technical vision for a robust data environment supporting Netflix's finance domain and partner with business, science, research, and engineering teams to deliver a shared vision.

You will coach and develop the team, balancing immediate partner needs with long-term data strategy, while driving scalable, reliable data systems across Netflix’s financial

Qualifications

• Proven track record leading data teams.

Responsibilities

• Provide technical vision to build a robust data environment for Netflix finance.

Skills

Data leadership

People management

Mentorship

Data pipelines

ETL

Enterprise data architecture

Recruiting

Job description

Data Engineering Manager

Location: Atlanta, USA | Company: Netflix | Salary: $20-30 per hour

Overview

Netflix is a global streaming platform with more than 230 million subscribers in 190+ countries, delivering TV series, movies, and original content across a wide range of genres and languages.

Responsibilities

• Provide technical vision and direction to build a robust data environment that enables Netflix to use data across finance.
• Build strong connections across business, science, research, and engineering.
• Balance immediate partner needs versus longer‐term vision.
• Lead a group of data engineers, researchers, and data scientists to execute a shared vision between research, design, and partners.
• Develop and coach the team through strategic insight and honest feedback.
• Build a scalable and resilient data environment for Netflix's entire financial ecosystem.

Qualifications

• Experienced data leader with a proven track record building and leading high‑quality, data‑centered teams.
• Demonstrated history of managing large and complex data engineering teams.
• Strong mentorship and coaching skills, guiding engineers to make informed architectural choices and improve code quality.
• Passionate about execution and speed of delivery, taking responsibility beyond the scope of one's own team when needed.
• Deep technical knowledge of data pipelines, ETL processes, and enterprise data architecture.
• Ability to maintain precision and quality during rapid growth.
• Proven recruiting expertise and commitment to continually raise standards for excellence.
• Dedication to data integrity and a focus on the subtle details of running operations.