Sr Digital Marketing Operations Analytics Manager

UPS

About The Position

UPS Digital is evolving from channel‑level reporting to a centralized Marketing Data Mart that serves as a single, governed source of truth across awareness, acquisition, activation, and conversion. The Senior Digital Marketing Operations Analytics Manager will serve as the single point of accountability for designing and governing a scalable marketing data architecture, integrating multiple external platforms (Adobe Analytics, paid media agencies, LinkedIn, Google, Bing, BlueConic, CRM, and more), and ensuring the data remains clean, flexible, and performance‑ready as the ecosystem expands. This role partners closely with other roles in Marketing, BIA, Data Science, Revenue Operations, and external vendors to translate marketing needs into scalable, reusable data solutions. Acting as the bridge between strategy and execution, this role builds and maintains trusted dashboards, strengthens data hygiene, enables scalable audience building, and supports advanced analytics, including propensity modeling. The role combines analytics leadership with data engineering fluency. This role will own the end‑to‑end marketing data model (prospects and customers), define ingestion standards, guide vendor integrations, and operationalize insights through Power BI dashboards that directly inform how success is measured by marketing efficiency, optimized investments decisions, and enabled self-service insights across the organization.

Requirements

Bachelor’s degree in Marketing Analytics, Data Science, Information Systems, Business, or equivalent professional experience.
Experience supporting marketing automation and/or audience segmentation workflows, including creation of data structure, campaign measurement and data flows between systems.
Experience in marketing analytics, marketing operations, or digital analytics, with demonstrated ownership of reporting and measurement outputs.
Hands‑on experience working with CRM data used for marketing measurement and activation.
Proven ability to translate marketing needs into clear requirements, metrics, dashboards, and actionable insights through cross‑functional partnership.
Must be a U.S. Citizen or National of the U.S., an alien lawfully admitted for permanent residence, or an alien authorized to work in the U.S. for this employer.

Nice To Haves

Experience acting as a data product owner for marketing analytics or Marketing Technology platforms.
Experience with Adobe Analytics, Google analytics and other marketing measurement platforms.
Experience building and governing audience traits, segments, and activation rules across paid and CRM channels.
Familiarity with advanced analytics such as propensity/predictive modeling, automated insights/anomaly detection, or performance forecasting.
Experience with BI and visualization tools for executive and self‑service reporting; comfort operating in enterprise‑scale environments.

Responsibilities

Own marketing data architecture end‑to‑end, partnering with the BIA and Data Science teams to design, document, and govern core marketing datasets and how they connect across systems and channels.
Establish and maintain a “source of truth per metric” approach, ensuring metric definitions, lineage, and ownership are clear and consistent.
Define governance standards for marketing measurement and activation, ensuring data is usable, trusted, and scalable.
Build and maintain marketing dashboards in partnership with BIA/Data Science, including executive and working‑level views that clearly distinguish KPIs vs. operational diagnostics.
Document for each dashboard metric: source system, refresh frequency, and whether retrieval is manual vs. automated; continuously improve reliability and repeatability.
Develop measurement frameworks that convert data into decisions, highlighting what’s working, why it’s working, and what to do next.
Own data hygiene practices that improve marketing data completeness, accuracy, consistency, and usability across reporting and activation workflows.
Establish standards and monitoring for common issues (duplication, inconsistent tagging, broken mappings, incomplete coverage) and coordinate remediation with analytics/engineering partners.
Drive operational discipline in inputs that impact reporting quality (e.g., consistent campaign tagging/UTM practices in partnership with analytics/ops).
Collaborate with Data Science to define requirements, operationalize, and maintain advanced analytics capabilities (e.g., propensity/predictive models, automated insights, anomaly detection).
Partner with Marketing Operations and channel owners to build and govern scalable audiences: traits, segments, activation rules, and repeatable processes that support campaign execution.
Ensure audience definitions are reusable, well‑documented, and measurable, enabling consistent targeting and performance evaluation across programs.