Engineering Director- Ads Measurement (AdTech)

Location: Mountain View, CA, United States; hybrid work with select days in a LinkedIn office

Salary: $231,000–$378,000 per year, plus potential bonus, stock, benefits, and other incentive compensation.

Company

LinkedIn operates a large professional network and a global B2B advertising platform that helps organizations grow.

What you will do

• Own the end-to-end measurement strategy for LinkedIn Marketing Solutions Ads Measurement, including hypotheses, experiment design, lift estimation, and causal inference.
• Define experimentation guardrails covering randomized holdouts, multi-cell designs, geo tests, sequential testing, and power planning.
• Lead incrementality measurement across funnel stages and quantify lift for conversions, leads, and revenue outcomes.
• Architect privacy-aware attribution methods and deliver resilient signals with robust uncertainty estimates.
• Partner with Product Management, Engineering, Data Science, Privacy, Legal, and Compliance to build telemetry, experiment platforms, APIs, dashboards, and reporting workflows.
• Build and retain a high-performing measurement organization, establish operating rhythms, and communicate outcomes to executives and customers.

Requirements

• Bachelor's degree in Computer Science, Operations Research, Statistics, Economics, or a related quantitative field.
• 10+ years of experience in leadership positions.
• Experience designing scalable, reliable infrastructure for marketing technology platforms, including data pipelines, eventing systems, and integrations across adtech, CRM, and analytics ecosystems.
• Experience delivering end-to-end solutions for high-QPS systems and massive datasets.
• Experience managing teams of 50+ people, including first- and second-line managers.
• Understanding of large-scale engineering systems, big data technologies, distributed systems, streaming, statistical methods, and experimental design.

Nice to have

• AI/ML experience applied to advertising.
• Publications at conferences or patents.
• Experience with Hadoop, Spark, distributed key-value stores, recommender systems, and related technologies.

Culture & Benefits

• Hybrid work structured around business and team needs.
• Health and wellness programs for employees and their families.
• Generous time away from work for employees at all levels.
• Potential annual performance bonus, stock, and additional benefits.
• Commitment to inclusive, accessible, and equitable employment practices.