Product Manager

About the role We are hiring a Product Manager — Household Data Products to own a portfolio of data products within Target's Household product line: from household definitions and taxonomy, through certified datasets, pipelines, quality and governance, to the applications that Media, Promotions, Merchandising and Loyalty teams use to make decisions. Household is how Target understands its guests as the real-world units that shop together. This role takes the household foundation and turns it into trusted, reusable data products and decision-ready applications — answering questions like which households we acquired, retained or reactivated, what drove it, and how we should market, promote and assort for them. This is a hands-on role that works closely with Data Engineering, Analytics, Data Science, Identity and business partners. You will partner with DE day-to-day across a medallion (Bronze/Silver/Gold) architecture, shape schemas and data contracts, and make sure household data products are trusted, well-governed and adopted. The core job is to translate technical capability into business outcomes. What you’ll own Household Foundations – Must Have You will help build and own the household foundation layer that every downstream use case depends on: stable, certified household datasets built on the enterprise household identity (owned by the Identity team), with consistent definitions that business partners can trust and reuse. • Household lifecycle definitions and formats — acquisition, retention, reactivation and new-to-category — agreed with Analytics and Finance and published as certified data products. • Household attributes and taxonomy — life stage, composition, demographics, interests and purchase behaviour, including third-party enrichment — with clear ownership, lineage and refresh cadence. • Household-level enterprise KPIs such as household-based conversion, taken from definition through UAT, sign-off and production. Household Applications – Must Have You will help turn the foundation into applications that change decisions across the enterprise, delivering against a roadmap shaped with your manager and business partners: • Media — map household cohorts to the campaigns they were exposed to, starting with diagnostics and extending to Roundel (retail media) audiences and measurement. • Promotions — connect households to promotion performance so promo teams can see who a promotion actually reached and moved. • Merchandising — household views of newness-led acquisition and assortment relevancy by life stage. • Enterprise growth — an acquisition and reactivation waterfall across drivers (marketing including Roundel, promotions, brand marketing, newness and assortment, new stores), plus who the acquired households are. Analytics & Data Fluency — Must Have Strong working knowledge of analytics and data concepts, with the ability to partner effectively with Analytics and Data Science teams. You should be comfortable with: • Household and guest-level analytics, cohorts and segmentation • Entity resolution and identity concepts (guest-to-household mapping, match rates, stability) • Data aggregation and dimensional modelling • Data quality, reconciliation and metric definitions in a semantic layer • Privacy, consent and responsible use of guest and household data Building data products with Data Engineering You work hand-in-hand with Data Engineering to turn requirements into real datasets and pipelines — translating business needs into clear specs and data contracts, prioritising the backlog, and making trade-off calls with DE on design, cost and sequencing. Platform & ecosystem stewardship Solid understanding of our data platform and cloud environment (GCP, BigQuery, Power BI). You make household data e