Analytics Engineer 5 - Ads Identity & Signals

Netflix is hiring an Analytics Engineer for its Ads Identity & Signals team. The role builds analytics and data infrastructure for identity graph construction and matching, including data models, pipelines, metrics, and dashboards that make identity health visible and actionable.

Responsibilities:

• Design, build, and maintain the data models and pipelines that support identity graph construction, entity matching, and identity resolution across first-party and third-party signals
• Partner with data engineering and software engineering to productionize matching logic, ensuring pipelines are scalable, well-tested, and monitored for data quality and drift
• Build metrics, dashboards, and analytics that quantify match rate, match quality, coverage, and graph stability, and that surface anomalies before they affect downstream campaigns
• Work closely with data science to evaluate and improve matching algorithms, providing the clean, well-documented data and features needed to test and iterate on models
• Manage and evaluate the analytics relationship with external identity providers (e.g., Experian, TransUnion, LiveRamp), including onboarding new sources, validating match performance, and monitoring ongoing data quality
• Translate identity graph and matching concepts — nodes, edges, match confidence, deterministic vs. probabilistic matching — into clear, actionable insights for product, sales, and other non-technical stakeholders
• Collaborate with product and cross-functional partners to define identity requirements, evaluate trade-offs (accuracy vs. coverage vs. privacy), and prioritize roadmap work
• Communicate technical decisions, trade-offs, and results clearly to both technical and non-technical audiences at all levels of the company

Requirements:

• 5+ years of experience as an analytics engineer, data engineer, or similar role working with large-scale data
• Experience working with graph data structures and graph-based data models (e.g., property graphs, graph databases, or graph analytics on top of relational/columnar stores)
• Familiarity with entity matching / identity resolution concepts — deterministic and probabilistic matching, fuzzy matching, blocking/candidate generation, and match quality evaluation
• Knowledge of, or direct experience working with, identity providers such as Experian, TransUnion, LiveRamp, or similar data/identity partners
• Strong SQL and Python skills, with experience building and maintaining production data pipelines
• Experience designing data models, metrics, and dashboards that make complex technical systems understandable to non-technical stakeholders
• Demonstrated ability to collaborate closely across data engineering, software engineering, data science, and product teams
• Ability to work independently, drive your own projects, and make compelling cases for prioritization
• Experience with ad-tech identity concepts — cross-device identity, household graphs, cookie/ID deprecation, or media measurement
• Experience with graph databases or graph-processing frameworks (e.g., Neo4j, Neptune, GraphFrames, or similar)
• Familiarity with our ML/data stack (Metaflow) or comparable large-scale data tooling
• Experience working with privacy-sensitive data and an understanding of relevant data governance and privacy considerations for identity data
• Experience applying GenAI to boost developer/analytics productivity