Product Manager - Household Data Products

Target Corporation India Pvt Ltd; Hyderabad; On-site; INR 1,400,000 - 2,200,000; Full time

Job summary

Target Corporation India Pvt Ltd is hiring a Product Manager for Household Data Products to own a portfolio of data products from household definitions and taxonomy to certified datasets, pipelines, quality and governance. You will work closely with Data Engineering, Analytics, Data Science and business partners to translate capabilities into business outcomes.

Responsibilities include shaping schemas, certifying data products, managing a tech backlog with DE, and enabling trusted, reusable data

Qualifications

• Strong working knowledge of analytics and data concepts, with the ability to partner with Analytics and Data Science teams.
• Experience with household data products, CDP / customer 360, identity, data platforms, or AdTech/MarTech in a retail context.
• Familiarity with data governance, privacy, and responsible use of guest and household data.
• Experience translating technical capability into measurable business outcomes.
• Clear communication with Data Engineering, Analysts, Data Scientists, and business stakeholders.

Responsibilities

• Translate requirements into clear specs and data contracts, prioritising the backlog with Data Engineering.
• Partner with DE day‑to‑day across medallion architecture (Bronze/Silver/Gold) to shape schemas and contracts.
• Own certification, quality monitoring, access controls and governance for the household product line.
• Collaborate with Marketing, Roundel, Loyalty, Promotions and Merchandising to gather and communicate progress.

Job description

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

• 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

• 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 mgmt 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
• third‑party data enrichment

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