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Dcomm data architect (madrid)

Madrid
Pepsico Deutschland
70.000 € al año
Publicada el Publicado hace 21 hr horas
Descripción

Overview

At PepsiCo International dCommerce team, we are building the next generation of innovative products and capabilities using emerging technologies to accelerate our business and gain back share. While tied closely to broader PepsiCo, the dCommerce group has a unique start‑up feel and defined values that embrace a more entrepreneurial mindset.

We are looking for an experienced Data Architect to shape the foundations of our rapidly scaling data ecosystem. As we expand across markets and evolve our capabilities, we need someone who can design data models, define metadata architecture, and establish the standards that make data accessible, usable and trusted across the organization.

This is a role for someone who wants to build the blueprint, not just inherit one. You’ll define how data is structured, documented, and governed across International Digital Commerce. You’ll represent dComm within Pepsico’s wider Data Architecture community while ensuring our unique needs are met. If you care about doing data right and want the scope to shape it from the ground up – this is that opportunity.


Responsibilities


Data Modelling and Architecture

* Design and maintain data models across the Digital Commerce domain, ensuring consistency, scalability and alignment with business semantics.
* Support in defining conceptual, logical, and physical architecture that supports data products and operational use cases.
* Own metadata management architecture ensuring data is discoverable, documented and understood across the organization.
* Establish data modelling standards and patterns that Data Engineering teams implement across regional pods.


Standards and Best Practices

* Define and evolve data architecture best practices across the Digital Commerce data.
* Work with the platform on reference design patterns for common scenarios (market integrations, new data sources, cross-functional data sharing).
* Review data designs proposed by Data Engineering, ensuring alignment.
* Drive improvement i.
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