E-Commerce Parts Ranges Data Specialist

12 ago - Rivalta di Torino
Stellantis

ABOUT THE ROLE

Scopra esattamente quali competenze, esperienze e qualifiche sono necessarie per avere successo in questo ruolo prima di candidarsi.
We are looking for an E-commerce – Parts Ranges Data Specialist to manage, standardize and optimize product data for parts and accessories across multiple systems and sources.

This role is essential to ensure high-quality, consistent and reliable product information for our e-commerce and marketplace platforms. You will work on complex product datasets, transforming heterogeneous information into a unified, structured and scalable data model that supports digital sales and customer experience.

WHAT YOU WILL DO
In this role, you will:

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- Collect, consolidate and harmonize Product Data from multiple sources (PIM systems, supplier feeds, ERP and internal databases).
- Map, merge and transform heterogeneous product information into a standardized data model.
- Clean, normalize and enrich product data, identifying and correcting missing, inconsistent or incorrect attributes.
- Enrich product information using reference databases,



taxonomies and external sources.
- Ensure compliance with data quality standards (completeness, accuracy, integrity).
- Maintain data governance documentation, including attribute dictionaries, naming conventions and validation rules.
- Collaborate with category managers, marketing teams, marketplaces and technical stakeholders to ensure aligned and reliable product content.
- Operate and optimize PIM/MDM systems, supporting automation of data import, validation and enrichment workflows.
- Monitor data quality KPIs and contribute to continuous improvement of tools, processes and controls.

WHO YOU ARE
You are a structured and detail-oriented professional with a strong interest in product data and digital environments. You bring:

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- 3-5 years of experience in Product Data Management, PIM/MDM, Data Engineering or ETL‑focused roles.
- Experience in data extraction, transformation and validation.

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