Director, Growth Data Engineering

About the Director, Growth Data Engineering Role at Netflix

At Netflix, our mission is to entertain the world. We are writing the next episode by pushing the boundaries of storytelling, global fandom, and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when creativity, intuition, and cutting-edge technology merge. Come be a part of what’s next.

In this role, you will lead a team of talented engineers building big data pipelines and services. These systems utilize distributed computing tools like Spark and Flink to power machine learning models, experimentation, analytics, and dashboards. Your team's work will impact various growth-related domains, including plans and pricing, identity, signup flow optimization, payments, and partnerships.

You will collaborate closely with cross-functional teams, including product engineers, data scientists, and business stakeholders, to help grow Netflix. The data your team produces will directly improve the customer experience and inform future product strategy.

Responsibilities

• Provide guidance and mentorship to managers and individual contributors on the team.
• Develop strong relationships with data science, engineering, and business partners, enhancing data leverage at Netflix.
• Help nurture the broader data engineering community at Netflix, collaborating with senior leaders.
• Expand your team by attracting diverse talent that can push our technical boundaries.
• Foster an inclusive environment, where all points of view are welcomed and encouraged.
• Be a thoughtful leader, driving both technical and business priorities and roadmaps.

Specific Qualifications

• Many years of experience leading engineering teams that design and build distributed systems, including for real-time and customer-impacting applications.
• Experience hiring and mentoring high-caliber, data-focused engineers with diverse technical strengths and backgrounds.
• High-energy self-starter with a passion for data, thriving in a fast-paced environment.
• Strong business acumen and interest in contributing to roadmaps and strategy discussions.
• Exceptional communication skills, able to translate technical concepts into easy-to-understand language for business partners.
• Familiarity with machine learning and/or experimentation (A/B) testing is a plus.
• Experience working in a growth-related domain (e.g., pricing, identity, payments, partnerships) is a plus.

Compensation & Benefits

Netflix's compensation structure typically consists solely of an annual salary without bonuses. You have the flexibility to choose how much of your compensation you want in salary versus stock options each year. Compensation is determined by market indicators, your specific job family, background, skills, and experience within a competitive market range. The range for this role is $705,000.00 - $1,600,000.00, which may vary based on location.

Netflix provides comprehensive benefits, including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. Paid leave of absence programs are also offered. Full-time hourly employees accrue 35 days annually for paid time off, while full-time salaried employees are immediately entitled to flexible time off. More details on benefits are available on the Netflix careers site.

Netflix Culture & Inclusivity

Netflix fosters a unique culture and environment. Inclusion is a core Netflix value, and we strive for a meaningful interview experience for all candidates. If you require an accommodation or adjustment for a disability or any other reason during the hiring process, please reach out to your recruiting partner.

We are an equal-opportunity employer, celebrating diversity and recognizing its role in building stronger teams. We approach diversity and inclusion seriously and thoughtfully, without discrimination on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Key skills/competency

• Data Engineering
• Distributed Systems
• Big Data Technologies
• Spark
• Flink
• Machine Learning
• Experimentation (A/B Testing)
• Leadership & Mentorship
• Business Acumen
• Data Pipeline Development