Technical Program Manager (Marketing Data)
New
R
RearcMarketing data
Location: Remote (USA)Full-TimeManager
Salary not disclosed
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Job Details
- Experience
- 8+ years of program or project management experience, with at least 4 years leading technical data, analytics, or platform programs.
- Required Skills
- Data modeling
Requirements
- Bring 8+ years of program or project management experience.
- Have at least 4 years of experience leading technical data, analytics, or platform programs.
- Demonstrate marketing domain expertise and the ability to define data KPIs from a marketer's perspective.
- Have experience with campaign performance, attribution, customer acquisition and retention, segmentation, and audience measurement.
- Have delivered marketing data programs such as customer data platforms, marketing data lakes, campaign analytics, or marketing measurement and attribution.
- Have working knowledge of marketing technology, especially Salesforce Marketing Cloud, Data Cloud, and Sales Cloud, and Adobe Analytics.
- Understand how data moves from marketing tools into an analytics platform.
- Understand data pipelines, data modelling, and lakehouse concepts; Databricks experience is a strong plus.
- Have a track record leading distributed teams across time zones, ideally including teams in the US and India.
- Be confident managing senior stakeholders in large, regulated enterprises; financial services or payments experience is preferred.
- Demonstrate delivery discipline across scope, timelines, risks, dependencies, and status reporting.
- Communicate effectively with CMOs, marketing analysts, and data engineers.
Responsibilities
- Translate marketers' questions into KPIs, metrics, and data requirements for the engineering team.
- Own engagement scope, roadmap, timelines, and milestones; identify and resolve risks and blockers.
- Coordinate a six-person data engineering team across the US and India.
- Serve as the primary day-to-day contact for marketing and technology stakeholders.
- Run status meetings, report progress, and manage client expectations.
- Partner with engineering leads on marketing-system ingestion, data modelling, and platform design.
- Help marketing teams trust and use delivered data, dashboards, and models.
- Identify opportunities for the client to get more value from its data and AI investment.
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