Software Engineer 5 - Ads Identity Graph

Netflix•Los Angeles, CA

5d•$388,000 - $558,000

About The Position

Netflix launched a new ad-supported tier in November 2022 to offer members more choice in how they consume their content. This new tier allows Netflix to attract new members at a lower price point while also creating a compelling path for advertisers to reach deeply engaged audiences. The Netflix Ads Identity Graph team develops the Netflix Ads Identity Graph and Identity Resolution services. The team's main objectives are to provide flexible and accurate Identity Resolution services and increase identifier coverage for better matching of advertiser and partner data, while ensuring a strong commitment to data protection and member privacy. As a Software Engineer on the Ads Identity Graph team, you will build systems to deliver the right ad to the right person at the right time leveraging advanced targeting techniques while respecting Netflix member privacy and consent choices. In this dynamic and innovative environment, your contributions will have a significant impact on how Netflix protects member data and privacy. You will collaborate with a team of talented professionals who are deeply passionate about technology and privacy, fostering a culture that values creativity, diversity, and continuous learning.

Requirements

Hands-on experience designing, developing, and maintaining large-scale Identity Graphs and Identity Resolution services used in advertising or marketing technology.
Proven ability to implement and operate both deterministic and probabilistic identity resolution in batch (offline) and near-real-time (online) systems, balancing precision, recall, and latency.
Experience architecting and integrating identifier collection flows into downstream identity pipelines in a privacy-conscious way.
Strong background in integrating identity signals with DSPs and other programmatic platforms.
Practical experience managing identity integrations with data clean rooms (e.g., privacy-safe joins, audience matching, and measurement) while preserving data minimization principles.
Deep understanding of data governance, privacy, and consent management within an identity framework, and a track record of embedding these requirements into system design and operations.
Proven experience in handling data at extremely large volumes with big data tools like Spark, and building high throughput low latency distributed systems that utilized the big data.
Ability to thrive in a fast-paced, dynamic environment and effectively manage multiple priorities.
Knowledge of the ad tech and advertising landscape, including programmatic advertising and digital marketing trends.
Excellent communication, negotiation, and relationship-building skills, with the ability to work collaboratively with cross-functional teams.

Nice To Haves

Experience working in the CTV space and knowledge of its unique constraints.
Experience building machine learning modeled targeting with automated objective based optimization.
Experience with targeting experimentation.
In-depth knowledge of regional privacy regulations, e.g. GDPR (General Data Protection Regulation), CCPA (California Consumer Privacy Act), and CPRA (California Privacy Rights Act).
Experience with Privacy Enhancing Technologies (PETs)

Responsibilities

Build systems to deliver the right ad to the right person at the right time leveraging advanced targeting techniques while respecting Netflix member privacy and consent choices.
Contribute to protecting member data and privacy in a dynamic and innovative environment.
Collaborate with a team of talented professionals passionate about technology and privacy.
Design, develop, and maintain large-scale Identity Graphs and Identity Resolution services used in advertising or marketing technology.
Implement and operate both deterministic and probabilistic identity resolution in batch (offline) and near-real-time (online) systems, balancing precision, recall, and latency.
Architect and integrate identifier collection flows into downstream identity pipelines in a privacy-conscious way.
Integrate identity signals with DSPs and other programmatic platforms.
Manage identity integrations with data clean rooms (e.g., privacy-safe joins, audience matching, and measurement) while preserving data minimization principles.
Handle data at extremely large volumes with big data tools like Spark, and build high throughput low latency distributed systems that utilized the big data.
Work in a fast-paced, dynamic environment and effectively manage multiple priorities.
Communicate, negotiate, and build relationships, with the ability to work collaboratively with cross-functional teams.