Manager, Expense Data Engineering

Netflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.

The Team

The Membership & Finance Data Engineering team is at the heart of Netflix's financial and member data ecosystem. We build foundational datasets and data products that power critical business operations, financial reporting, and strategic analytics. As Netflix grows in scale and complexity, so does the need for clear visibility into our expenses to ensure we are investing wisely and operating efficiently.

To meet this need, we have a dedicated team to focus specifically on Expense Data. This team plays a crucial role in fostering a culture of financial responsibility by owning and optimizing all expense-related data. They cover diverse and critical subject areas such as payment processing fees, content actuals and amortization, tax, and people costs. By providing accurate, timely, and insightful data, this team enables leaders across Netflix to forecast and manage costs effectively and make informed decisions that impact the bottom line.

The Role

We are looking for an innovative and strategic engineering leader to build and lead the Expense Data Engineering team. You will guide a talented group of data engineers to build world-class expense data models that provide a comprehensive view of costs across the company. This is a unique opportunity to shape a critical data domain and potentially grow the role's scope to unify all expense insight workstreams. You will partner with senior leaders across the company to build data solutions that drive efficiency and strategic cost management.

In this role, you will:

• Lead and Inspire: Hire, coach, and grow a high-performing and inclusive team of data engineers, fostering their technical and professional development.

• Define the Vision: Shape and execute an impact-oriented technical vision for the Expense data domain, with a strategic eye toward a unified view of company-wide spend, including all people, content, and operational costs.

• Execute with Excellence: Lead the team in designing, building, and scaling robust and auditable data pipelines and models, with a keen eye for data quality and SOX compliance.

• Partner and Influence: Build strong relationships and collaborate effectively with a wide range of stakeholders, including leaders in Finance (FP&A, F&S), Talent (Analytics & Engineering), Content Accounting, Product Management, and Internal Audit teams.

• Drive Business Impact: Oversee key initiatives such as building out the analytics powered by a new Netflix Tax Platform, Content Finance Controllership (CFC) data model, improving analytics for payment processing fees, evolving our people data foundations, and enabling new forecasting and reporting capabilities through the Finance Data Universe (FDU).

• Innovate and Optimize: Identify opportunities to re-architect systems, push data quality checks upstream, and leverage new platform capabilities to improve efficiency and provide deeper insights into our cost structures.

The Ideal Candidate:

• You have proven experience leading data engineering teams, ideally with exposure to financial or accounting data systems. Experience with SOX-compliant systems is a major plus.

• You possess strong technical acumen in data warehousing, data modeling, and large-scale data processing (e.g., Spark). You can set a high technical bar and guide your team through complex architectural decisions.

• You are a strategic thinker who can navigate a complex and fragmented data space and drive towards a consolidated, coherent vision. Experience with people/HR data or Tax data is a plus.

• You have exceptional communication and stakeholder management skills, capable of building consensus and driving alignment across multiple senior-leader organizations.

• You are detail-oriented and have a passion for data quality and financial accuracy, understanding the critical importance of this data domain.

• You are excited by the challenge of building foundational data products that provide clarity on business expenses and empower the company to operate with greater financial discipline.

Our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $360,000 - $920,000.

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. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more detail about our Benefitshere.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversitybuilds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate 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.

Job is open for no less than 7 days and will be removed when the position is filled.