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# Analytics Engineer 5 - Ads Identity & Signals

- **Company:** Netflix, Inc.
- **Location:** Beverly Hills, CA, United States
- **Experience:** Expert
- **Salary:** $330,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Big Data, Information Engineering, Data Governance, Data Structures, Graph Database, Python (Programming Language), Neo4j, Operational Databases, Standard Sql, Software Engineering, Data Management, User Identification
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/analytics-engineer-5-ads-identity-signals-beverly-hills-ca--8e7c4b30-b283-454a-8fe0-b8839874fd8e

## About the Role

Storytelling, Leading Edge Technology, Ecosystems, Campaigns, Relationship Management, Identity Data Management, Sales Pipeline, Metrics, Reporting Dashboards, Construction, * 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.
 * Embodies the Netflix values while bringing a new perspective to continue improving our culture.

Nice To Have

 * 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.

## Description

* 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.