Analytics Engineer 5 - Ads Identity & Signals
About The Position
Netflix is building an in-house ad-tech ecosystem for its ad-supported tier. The Identity & Signals team develops the identity foundation for the ads business, including the graph and matching systems used to recognize people or households across signals, devices, and partner data sources, and to determine which signals can be responsibly and accurately used for targeting, measurement, and reporting. This role builds the analytics and data infrastructure supporting identity matching and graph construction. The Analytics Engineer designs tables, pipelines, and metrics that help the team and its stakeholders understand match quality, coverage, and drift. The work spans raw signal ingestion, matching logic, graph construction, and dashboards and data products that make identity health visible and actionable across the company. The role also partners with engineering, data science, product, and external identity providers, and communicates technical decisions and results to technical and non-technical stakeholders.
Requirements
- 5+ years of experience as an analytics engineer, data engineer, or in a similar role working with large-scale data.
- Experience with graph data structures and graph-based data models, such as property graphs, graph databases, or graph analytics on relational or columnar stores.
- Familiarity with entity matching and identity resolution concepts, including deterministic and probabilistic matching, fuzzy matching, blocking or candidate generation, and match quality evaluation.
- Knowledge of or direct experience working with identity providers such as Experian, TransUnion, LiveRamp, or similar data or 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 and drive projects.
- Embodies Netflix values and brings a new perspective to improving the company culture.
Nice To Haves
- Experience with ad-tech identity concepts, such as cross-device identity, household graphs, cookie or ID deprecation, or media measurement.
- Experience with graph databases or graph-processing frameworks such as Neo4j, Neptune, or GraphFrames.
- Familiarity with Netflix's ML/data stack, Metaflow, or comparable large-scale data tooling.
- Experience working with privacy-sensitive data and understanding of relevant data governance and privacy considerations for identity data.
- Experience applying GenAI to improve developer or analytics productivity.
Responsibilities
- Design, build, and maintain data models and pipelines for 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 and ensure pipelines are scalable, tested, and monitored for data quality and drift.
- Build metrics, dashboards, and analytics to quantify match rate, match quality, coverage, and graph stability, and surface anomalies before they affect downstream campaigns.
- Work with data science to evaluate and improve matching algorithms, providing clean, documented data and features for model testing and iteration.
- Manage and evaluate analytics relationships with external identity providers, including onboarding sources, validating match performance, and monitoring ongoing data quality.
- Explain identity graph and matching concepts, including nodes, edges, match confidence, and deterministic versus probabilistic matching, as actionable insights for non-technical stakeholders.
- Collaborate with product and cross-functional partners to define identity requirements, evaluate accuracy, coverage, and privacy trade-offs, and prioritize roadmap work.
- Communicate technical decisions, trade-offs, and results clearly to technical and non-technical audiences across the company.
- Independently drive projects and make compelling cases for prioritization.
Benefits
- Comprehensive health plans
- Mental health support
- 401(k) retirement plan with employer match
- Stock option program
- Disability programs
- Health savings and flexible spending accounts
- Family-forming benefits
- Life and serious injury benefits
- Paid leave of absence programs
- Full-time hourly employees accrue 35 days annually for vacation, holidays, and sick paid time off
- Full-time salaried employees are immediately entitled to flexible time off
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
