Analytics Engineer 5 - Ads Identity & Signals

Jobgether; United States; Remote; USD 330,000 - 566,000; Full time

Benefits offered by this job

Flexible salary & equity

Remote work in the United States

Healthcare coverage

Mental health support

401(k) matching

Stock options

Disability protection

Paid leave

Flexible time off

Family-forming benefits

Job summary

Jobgether in the United States is seeking an Analytics Engineer 5 – Ads Identity & Signals to design and build scalable data models, pipelines, and analytics systems for identity resolution across devices and data sources, including first-party and third-party signals.

You will partner with data engineering, software engineering, data science, and product teams to evaluate matching algorithms, monitor data quality, define metrics, and deliver measurable insights that drive advertising targeting,

Qualifications

• Five+ years of professional experience as Analytics Engineer, Data Engineer, or similar role.
• Experience with graph data structures and graph databases.
• Understanding of deterministic and probabilistic matching, fuzzy matching, and match-quality evaluation.
• Strong SQL and Python for production-grade data pipelines.
• Ability to design data models, metrics, and dashboards for non-technical audiences.
• Collaborative cross-functional work experience.

Responsibilities

• Design, build, and maintain scalable data models and pipelines for identity graph construction and identity resolution across data sources.
• Partner with data and software engineers to productionize identity-matching logic and ensure data quality and performance.
• Develop metrics, dashboards, and tools to measure match rates, identity coverage, and graph health.
• Establish monitoring to detect anomalies and changes in matching performance.
• Collaborate with data scientists to evaluate and improve identity-matching algorithms.
• Evaluate external identity data providers and onboard new data sources.
• Translate identity graph concepts into clear insights for product and business stakeholders.
• Define identity requirements with cross-functional partners and prioritize roadmap initiatives.

Skills

SQL

Python

Data pipelines

Data modeling

Cross-functional collaboration

Tools

Neo4j

Amazon Neptune

GraphFrames

Job description

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for an Analytics Engineer 5 – Ads Identity & Signals based in the United States.

Join an innovative advertising technology team building the data infrastructure that powers identity resolution and audience insights across a global streaming platform.
In this senior-level role, you will design and develop scalable data models, pipelines, and analytics systems that help recognize individuals and households across devices, signals, and external data sources.
Your work will directly influence advertising targeting, campaign measurement, reporting accuracy, and the reliability of identity data products.
Collaborating with data engineering, software engineering, data science, and product teams, you will transform complex identity-matching processes into measurable, actionable insights.
You will help evaluate matching algorithms, monitor data quality, and establish metrics that reveal identity coverage, match accuracy, and system performance over time.
This role offers the opportunity to shape foundational analytics capabilities within a growing advertising technology ecosystem, where technical ownership and independent problem-solving are highly valued.
If you combine strong engineering expertise with analytical thinking and effective communication, you can make a significant impact on the future of data-driven advertising.

Accountabilities

• Design, build, and maintain scalable data models and production pipelines supporting identity graph construction, entity matching, and identity resolution across first‑party and third‑party data sources.
• Partner with data engineers and software engineers to productionize identity‑matching logic, ensuring pipelines are reliable, scalable, well‑tested, and monitored for data quality issues and performance drift.
• Develop and maintain metrics, dashboards, and analytical tools that measure match rates, matching accuracy, identity coverage, graph stability, and overall system health.
• Establish monitoring frameworks to detect anomalies, data inconsistencies, and changes in matching performance before they affect advertising campaigns or downstream reporting.
• Collaborate with data scientists to evaluate, validate, and improve identity‑matching algorithms by providing reliable datasets, well‑documented features, and analytical insights.
• Manage the analytical evaluation of external identity providers, including onboarding new data sources, validating matching performance, and monitoring ongoing data quality and reliability.
• Translate complex identity graph concepts, including nodes, edges, match confidence, and deterministic versus probabilistic matching, into clear insights for product, sales, and other non‑technical stakeholders.
• Work with product managers and cross‑functional partners to define identity requirements, evaluate trade‑offs between accuracy, coverage, and privacy, and prioritize roadmap initiatives.
• Communicate technical decisions, analytical findings, system limitations, and business implications effectively to stakeholders at all organizational levels.
• Contribute to the development of reliable data products and standardized metrics that improve transparency and trust in identity‑related systems.
• Identify opportunities to improve data infrastructure, analytical workflows, and engineering productivity through automation and emerging AI‑powered tools.
• Take ownership of complex analytical projects, independently define solutions, and advocate for priorities that improve identity data quality and advertising performance.

Requirements

• At least five years of professional experience as an Analytics Engineer, Data Engineer, or in a similar technical role working with large‑scale data systems.
• Experience working with graph data structures and graph‑based data models, including property graphs, graph databases, or graph analytics built on relational or columnar data platforms.
• Understanding of entity matching and identity resolution methodologies, including deterministic and probabilistic matching, fuzzy matching, blocking and candidate generation, and match‑quality evaluation.
• Strong proficiency in SQL and Python, with demonstrated experience developing, deploying, and maintaining production‑grade data pipelines.
• Experience designing data models, analytical metrics, and dashboards that make complex technical systems understandable and actionable for non‑technical audiences.
• Ability to collaborate effectively with data engineering, software engineering, data science, and product teams to deliver scalable, cross‑functional solutions.
• Strong analytical and problem‑solving skills, with the ability to investigate complex data issues, evaluate technical trade‑offs, and develop robust solutions.
• Excellent written and verbal communication skills, including the ability to explain technical concepts, justify decisions, and present findings to both technical and business stakeholders.
• Demonstrated ownership and initiative, with the ability to work independently, manage competing priorities, and build compelling cases for project prioritization.
• A collaborative mindset, sound professional judgment, and a commitment to contributing new perspectives while supporting an inclusive, high‑performance working environment.

Preferred qualifications

• Experience with advertising technology and identity‑related concepts, including cross‑device identity, household graphs, cookie and advertising identifier deprecation, or media measurement.
• Familiarity with graph databases and graph‑processing frameworks such as Neo4j, Amazon Neptune, GraphFrames, or comparable technologies.
• Experience with Metaflow or similar machine learning and large‑scale data infrastructure.
• Experience working with privacy‑sensitive data and an understanding of data governance, privacy requirements, and responsible identity data management.
• Experience using generative AI tools to improve analytics workflows, software development productivity, data exploration, and problem‑solving.
• Familiarity with external identity data providers such as Experian, TransUnion, LiveRamp, or similar organizations.

Benefits

• Competitive annual compensation: $330,000–$566,000, with the final offer determined by location, job family, experience, skills, and relevant market factors.
• Flexible salary and equity structure: Employees can choose annually how to allocate their compensation between cash salary and stock options, within the applicable compensation framework.
• Comprehensive healthcare coverage: Access to health insurance plans designed to support employees' medical needs.
• Mental health support: Resources and services to support mental and emotional well‑being.
• Retirement savings: A 401(k) retirement plan with employer matching.
• Stock option program: Opportunities to participate in the company's equity program.
• Disability protection: Access to disability benefits and programs.
• Health and Flexible Spending Accounts: Options to manage eligible healthcare and dependent‑care expenses.
• Family‑forming benefits: Support for eligible family‑building needs and related life events.
• Life and serious injury benefits: Financial protection for eligible employees and their families.
• Paid leave programs: Access to paid leave for qualifying circumstances.
• Flexible time off: Full‑time salaried employees receive flexible time off, supporting autonomy and work‑life balance.
• Remote work: Opportunity to work remotely from within the United States.
• High‑impact technical work: Help build foundational identity infrastructure and analytical capabilities within an evolving advertising technology business.
• Cross‑functional collaboration: Work with experienced professionals across data engineering, software engineering, data science, and product development.

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