Analytics Engineer 5 – Ads Identity & Signals

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and sustain data models and pipelines that facilitate the construction of identity graphs, entity matching, and identity resolution.

• Collaborate with data engineering and software engineering teams to implement scalable, rigorously tested matching logic while overseeing data quality and drift.

• Create metrics, dashboards, and analytics that assess match rate, match quality, coverage, and graph stability.

• Identify anomalies proactively to prevent impacts on downstream campaigns.

• Partner with data science to assess and enhance matching algorithms.

• Deliver clean, well-documented data and features for model testing and iterative development.

• Manage and assess analytics partnerships with external identity providers.

• Integrate new identity data sources, validate match performance, and continuously monitor data quality.

• Convert identity graph and matching concepts into actionable insights for product, sales, and non-technical stakeholders.

• Work in conjunction with product and cross-functional teams to define identity requirements, assess accuracy, coverage, and privacy trade-offs, and prioritize tasks on the roadmap.

• Effectively communicate technical decisions, trade-offs, and outcomes to both technical and non-technical audiences.

⛳️ Requirements

• A minimum of 5 years of experience as an analytics engineer, data engineer, or a similar position handling large-scale data.

• Proficiency in working with graph data structures and graph-oriented data models.

• Understanding of entity matching and identity resolution concepts, including deterministic and probabilistic matching, fuzzy matching, blocking/candidate generation, and match quality assessment.

• Experience with identity providers such as Experian, TransUnion, LiveRamp, or other similar data/identity partners.

• Strong skills in SQL and Python.

• Proven experience in creating and maintaining production data pipelines.

• Expertise in designing data models, metrics, and dashboards tailored for non-technical stakeholders.

• Ability to collaborate effectively with data engineering, software engineering, data science, and product teams.

• Capacity to work independently, lead projects, and present compelling prioritization cases.

• Familiarity with ad-tech identity concepts.

• Experience with graph databases or graph-processing frameworks such as Neo4j, Neptune, or GraphFrames.

• Knowledge of Metaflow or similar large-scale data tools.

• Experience handling privacy-sensitive data and understanding relevant data governance and privacy issues.

• Experience utilizing GenAI to enhance developer or analytics productivity.

🏝️ Benefits

• Comprehensive health plans.

• Mental health support.

• 401(k) retirement plan with employer matching.

• Stock option program.

• Disability programs.

• Health savings and flexible spending accounts.

• Family-forming benefits.

• Life and serious injury benefits.

• Paid leave of absence programs.

• Flexible time off for full-time salaried employees.