MarTech LiveRamp CleanRoom Engineer

Role: Clean Room Engineer
Location: Charlotte, NC / Dallas, TX / Jersey City, NJ (Hybrid – 3 days/week onsite)
Duration: 12 months

Job Overview:

We are seeking a Clean Room Engineer with a strong background in advertising measurement, marketing analytics, data science, or analytics engineering. The ideal candidate will combine hands-on expertise in SQL and Python with a solid understanding of digital advertising measurement, attribution, audience analytics, and privacy-safe data collaboration.

The candidate should be comfortable working with large-scale marketing datasets and translating advertising and campaign data into measurable business insights while operating within privacy and clean-room constraints.

Key Responsibilities:

• Develop and analyze advertising measurement solutions covering reach and frequency, campaign pacing, attribution, incrementality, media effectiveness, and audience performance.

• Build analytical queries and data models using advanced SQL and Python to support marketing and advertising measurement use cases.

• Design and implement measurement approaches for multi-touch attribution (MTA), marketing attribution, campaign performance, and media mix modeling (MMM).

• Analyze advertising campaigns across digital media channels and evaluate campaign reach, engagement, conversion, and effectiveness.

• Work with advertising ecosystems such as Meta, Google DV360, Google Marketing Platform, TikTok, Pinterest, Amazon Advertising, and similar platforms.

• Develop measurement solutions within privacy-safe data collaboration and clean-room environments.

• Work with platforms such as LiveRamp Clean Room/Safe Haven/Habu, Amazon Marketing Cloud, Amazon Clean Rooms, Google Ads Data Hub, GMP, Snowflake, or comparable technologies.

• Create clean-room analytical logic, including questions, queries, UDFs, and privacy-compliant analytical workflows within publisher or platform constraints.

• Apply privacy-safe aggregation techniques, including minimum group-size requirements, suppression rules, noise controls, and restricted data-access patterns.

• Support identity resolution use cases involving deterministic and probabilistic matching, persistent identifiers, RampID or equivalent IDs, and match-rate optimization.

• Build and maintain scalable data pipelines across AWS, Azure, or Google Cloud Platform environments.

• Use Python and/or Spark for data transformation, analytical processing, and pipeline development.

• Partner with marketing, media, analytics, data engineering, and business teams to translate measurement requirements into technical solutions.

• Validate analytical results and ensure measurement methodologies are accurate, reproducible, and aligned with business objectives.

• Follow applicable data privacy and regulatory requirements, including CCPA, GLBA, and applicable state privacy regulations.

• Document analytical methodologies, data models, clean-room logic, and technical processes.

• Troubleshoot data quality, query, pipeline, identity-matching, and measurement-related issues.

Advertising Measurement Experience:

Candidates should have hands-on experience with one or more of the following:

• Reach & Frequency Analysis

• Campaign Pacing

• Multi-Touch Attribution (MTA)

• Marketing Attribution

• Incrementality Testing

• Media Mix Modeling (MMM)

• Marketing Effectiveness

• Audience Analytics

• Campaign Performance Measurement

• Media Performance Analytics

• Conversion & Lift Analysis

Advertising & Media Platforms:

Experience with one or more of the following is highly desirable:

• Meta

• Google DV360

• Google Marketing Platform (GMP)

• TikTok

• Pinterest

• Amazon Advertising

• Other digital advertising and retail media platforms

Clean Room / Privacy-Safe Data Technologies:

Experience with any of the following is preferred:

• LiveRamp Clean Room / Safe Haven / Habu

• Amazon Marketing Cloud (AMC)

• Amazon Clean Rooms

• Google Ads Data Hub

• Google Marketing Platform

• Snowflake Data Sharing / Clean Room

• InfoSum

• Other privacy-safe data collaboration platforms

Note: Direct LiveRamp experience is preferred but not mandatory. Candidates with relevant advertising measurement and clean-room experience on other platforms can be considered.

Identity Resolution:

• Understanding of identity resolution and identity graph concepts.

• Experience with deterministic and probabilistic matching.

• Familiarity with RampID or equivalent persistent identifiers.

• Experience analyzing and improving identity match rates.

• Understanding of privacy-safe identity linkage across advertising and customer datasets.

Required Technical Skills:

• Advanced SQL

• Python

• Data Analytics

• Data Modeling

• Analytical Query Development

• Attribution & Measurement Logic

• Large-Scale Data Processing

• Cloud Data Platforms

• Data Pipeline Development

• Python and/or Spark

Preferred Qualifications:

• 5–7+ years of experience in data science, data engineering, marketing technology, advertising analytics, identity infrastructure, or related fields.

• 2+ years of hands-on experience working with data clean rooms or privacy-safe data collaboration environments.

• Experience developing clean-room questions, analytical queries, and/or UDFs, rather than only performing ETL or data ingestion.

• Strong understanding of privacy-preserving aggregation techniques, including suppression, minimum aggregation thresholds, and noise budgets.

• Experience supporting retail media, advertising agencies, consumer brands, or digital media organizations.

• Experience working with organizations such as Publicis, WPP, Omnicom, IPG, Dentsu, GroupM, Walmart, Target, Ulta Beauty, Kroger, Home Depot, Lowe's, Costco, CVS, or Walgreens is a plus.

• Strong communication and problem-solving skills with the ability to work across technical and marketing stakeholders.