Full-Time VP Technical Consulting - Panel Extracts
NielsenIQ is hiring a remote Full-Time VP Technical Consulting - Panel Extracts. The career level for this job opening is Manager and is accepting Chicago, IL based applicants remotely. Read complete job description before applying.
NielsenIQ
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About this JobWe are seeking a strategic and technically adept leader to head NielsenIQ’s Consumer Panel Data Extracts and Data Feed Practice.
This role will oversee the delivery of both disaggregated and aggregated consumer panel data, guide ingestion best practices for clients, and ensure ongoing servicing excellence across market research and media use cases.
The Vice President will report directly to the North American Consumer Panel Practice Leader and serve as a key member of the leadership team.
Responsibilities
- Lead the Consumer Panel Data Feed and Extract Delivery, Consulting, and Customer Success Team.
- Own the end-to-end delivery of consumer panel data extracts, ensuring accuracy, timeliness, and client usability.
- Provide technical consulting on ingestion strategies, schema design, and projection methodologies.
- Drive customer success through proactive engagement, issue resolution, and renewal support.
- Translate client Statements of Work (SOWs) into custom deliverables and manage recurring delivery schedules.
- Collaborate cross-functionally with product, go-to-market, customer success, and partner teams to evolve the practice.
- Lead the design and development of scalable delivery mechanisms—from legacy SFTP to modern clean room environments.
- Build and mentor a high-performing team focused on delivery excellence and client satisfaction.
Requirements:
- 3+ years working with disaggregated and aggregated consumer panel data.
- 3+ years leading technical delivery and customer success teams.
- 5+ years of management experience.
- 3+ years of direct client engagement experience.
- 2+ years working with clean rooms or modern data-sharing technologies.
- Proficiency in SQL, Python, and R.
- Deep understanding of: Purchase data metrics and demographic attributes, Schema optimization for ingestion, Projection factors and methodologies, Common client use cases for high-value data assets.