Product Manager

Target

Bengaluru

On-site

INR 2,400,000 - 3,200,000

Full time

2 days ago

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Job summary

Target is hiring a Product Manager for Household Data Products to own a portfolio of data products—from foundations and taxonomy to certified datasets, pipelines and governance—used by Media, Promotions, Merchandising and Loyalty teams to drive decisions.

You will work with Data Engineering and Analytics to translate requirements into data contracts, shape schemas, and ensure trusted, scalable, and adoption-ready data products across a medallion architecture.

Qualifications

3–5 years in product management (or 5+ years in closely related data, analytics or engineering roles) with experience on customer or household data products, CDP / customer 360, identity, data platforms, or AdTech/MarTech and retail media.
Strong understanding of customer and household analytics — lifecycle, segmentation, cohorts and life-stage modelling.
Familiarity with identity resolution and householding concepts, and with how household data powers audiences, measurement and personalisation.
Hands‑on experience working closely with Data Engineering to build datasets and pipelines — writing specs, shaping schemas and contracts, and prioritising a technical backlog.

Responsibilities

Own the Household Foundations and the downstream data products that support decision‑making across Marketing, Roundel, Loyalty, Promotions and Merchandising.
Partner with Data Engineering to translate business needs into data contracts, schemas and pipelines, and prioritise the backlog.
Collaborate with Analytics, Data Science and business partners to ensure data quality, governance and usable data products.
Translate technical capability into measurable business outcomes and communicate progress, trade‑offs and impact clearly to stakeholders and leadership.
Assist in shaping a roadmap for data products with cross‑functional alignment and governance considerations.

Skills

Product management

Analytics

Identity resolution

Data governance

Stakeholder management

Backlog prioritisation

Cross‑functional collaboration

Data modeling

Tools

GCP

BigQuery

Power BI

Job description

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.

About The Role

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 easy to discover, access and consume — through the certified gold layer, documented data products and self‑serve paths for analysts and downstream platforms.

Trust, governance & data quality — critical

Data governance and data quality are central to this role, not an afterthought. Household data drives audience targeting, measurement and executive reporting, so an unstable household ID or a wrong definition ripples across every team that uses it. You own certification, quality monitoring, access and consent controls for the household product line.

Stakeholder partnership

You will work with partners across Marketing, Roundel, Loyalty, Promotions and Merchandising to gather requirements, clarify competing asks, and communicate progress, trade‑offs and impact clearly to stakeholders and leadership.

What You’ll Bring

3–5 years in product management (or 5+ years in closely related data, analytics or engineering roles with product exposure), with experience on customer or household data products, CDP / customer 360, identity, data platforms, or AdTech/MarTech and retail media.
Strong understanding of customer and household analytics — lifecycle (acquisition, retention, reactivation), segmentation, cohorts and life‑stage modelling.
Familiarity with identity resolution and householding concepts, and with how household data powers audiences, measurement and personalisation.
Hands‑on experience working closely with Data Engineering to build datasets and pipelines — writing specs, shaping schemas and contracts, and prioritising a technical backlog.
Solid understanding of medallion architecture (Bronze/Silver/Gold) and modern data platforms (lakehouse, data mesh or federated architectures), including lineage and cost.
Strong grasp of data governance and data quality — certification, monitoring, access, privacy and consent — treated as critical, not optional.
Experience translating technical capability into measurable business outcomes and working effectively with cross‑functional partners without direct authority.
Strong product management practices and excellent communication with Data Engineering, Analysts, Data Scientists and business stakeholders.
Nice to have: exposure to marketing measurement (attribution, MTA, MMM), promotions or merchandising analytics, or third‑party data enrichment.

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