Senior Product Manager, Search & Social

Overview

The Technical Product Manager for Search and Social Advertising is a core member of the PMX PAS Product organization. This role bridges search and social media expertise, data/technology understanding, and product execution discipline to advance PAS' cross-channel analytics, reporting, and optimization capabilities.

Responsibilities

• Contribute to PAS roadmap across search and social media measurement (SEM, Youtube, social media and more), benchmarks, quality/brand safety insights, marketplace integrations, and manual workflow automations.

• Assess needs from agency activation teams, PMX Partnerships, and Analytics to prioritize features based on impact, feasibility, and user value.

• Support long-term platform evolution including marketplace integrations, improved data quality, and automated reporting expansions.

• Act as day-to-day Product Owner and SME (Subject Matter Experts) for one or more PAS development pods for search and social media advertising services and deliverables.

• Translate search and social media marketplace mechanics and product requirements into clear user stories, functional requirements, acceptance criteria, and technical dependencies.

• Groom to refine and define stories and tasks that can be transformed into agile tickets and tasks/sub-tasks.

• Bridge Product and Engineering on signal ingestion, business logic integration, taxonomy alignment, platform consistency and UX/UI.

• Discover, identify and define QA methodologies, data backfill/reprocessing, rollback, disaster recovery, observability C monitoring.

• Discover, identify and prevent/prepare for errors and failures (known and unknown/assumed).

• Work with internal technical, support and resource teams to enable PAS to deliver solutions.

• Collaborate closely with internal Datalake teams.

• Partner with Engineering on:

  • Data pipeline readiness
  • API integrations (search platforms, social media platforms, analytics vendors, marketplace partners)
  • Validation and QA for search and social media datasets
  • Troubleshooting discrepancies, mapping issues, and freshness problems
  • Define requirements for multiple reports and features
  • Maintain a clean, prioritized backlog and ensure sprint readiness with Engineering.

• Stakeholder Engagement

  • Work closely with search + social media and PAS Enablement and other internal teams to gather feedback and validate solutions.
  • Partner with PAS Enablement to support GTM and adoption through training materials, documentation, sample analyses, playbooks, and FAQs.
  • Partner with external ad-tech vendors (analytics, measurement partners) as needed.

• Search and Social Media Advertising Expertise

  • Serve as the internal SME on search and social media advertising mechanics involving platforms/resources such as Google Ads, Microsoft Ads, Search Ads 360, Google Analytics, Facebook, Instagram, Tik Tok, Snap, measurement partners, audience targeting partners.
  • Use this expertise to guide product decisions and validate analytical outputs.

Qualifications

• Experience 4–6+ years in product management, ad tech, marketing technology, search marketing advertising, social media advertising, or a related data-driven advertising role.

• Hands-on knowledge of search and social advertising, data management-engineering, reporting, campaign performance optimization.

• Strong understanding of bidding mechanics, auction logic, and platform-specific bidding processes and rules.

• Experience working with engineering teams on data or platform products (APIs, ETL pipelines, cloud technologies).

• Familiarity with tools such as Jira, Confluence, Tableau, Databricks, Snowflake, or similar.

• Excellent communication and stakeholder management skills across technical and non-technical groups.

• Ability to translate business needs into structured product requirements and clear deliverables.

Nice-to-Have

• Experience with programmatic advertising (display and video).

• Experience with data QA, mapping, and troubleshooting within programmatic datasets.

• Understanding of identity, audience targeting, or cookie-less strategies.

• Experience with cross-channel analytics or MMM/MTA inputs.