Data Architect (Data & AI)

Worldwide | Oct. 20, 2026

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Company: Grupo Mariposa

Country: Worldwide

Type: Remote

Employment: Full-time

Description: We are a multinational food and beverage corporation founded in 1885 with operations in more than 14 countries, with more than 15,000 employees.

About the company

Grupo Mariposa is a multinational food and beverage corporation, founded in 1885, with operations in more than 14 countries and more than 15,000 employees. We have the largest beverage portfolio in the region and strategic alliances with PepsiCo and AB InBev. We are organized into 4 business units: apex (transformation), cbc (distribution), beliv (innovation in beverages) and bia (food). We are looking for talents to join our expansion and growth strategy, sharing our desires and contributing their vision to achieve great results.

We are looking for the "Data Engineering Lead" to lead the corporate data platform in a multi-cloud environment, with a focus on Azure and support on Google Cloud Platform (GCP). This role defines, leads and scales the data engineering strategy for the region, ensuring a robust, governed and scalable platform for advanced analytics, BI and digital products in multiple countries.

Description

We are looking for a Junior Data Architect to join our architecture team, which provides transversal support to all data areas of the organization. You will work alongside senior architects in the design and evolution of the data platform in Azure and Databricks, learning to make data-driven decisions, define standards and accompany teams from design to production and incident resolution. It is an ideal role for someone based in data engineering who wants to take the step towards architecture, with a broader vision of the ecosystem.

Requirements

• 2 to 3 years of experience in Data Engineering, BI, Analytics Engineering or a similar role.
• Practical experience in Azure, especially Azure Data Factory (ADF) and Azure Data Lake Storage (ADLS).
• Practical experience with Databricks: Delta Lake, Databricks Workflows and knowledge of Unity Catalog.
• Good command of Python, PySpark and SQL.
• Experience with Terraform and CI/CD, ideally Terraform Cloud and GitHub Actions, to deploy jobs, clusters and permissions.
• Knowledge of relational and dimensional data modeling, and notions of NoSQL document bases (document and index modeling).
• Understanding of data architecture concepts. data: Lakehouse, medallion architecture (bronze/silver/gold), batch vs. streaming.
• Ability to document and communicate technical ideas clearly, both in writing and with diagrams.

Profile we are looking for

Systemic vision and curiosity to understand how the pieces of a complete platform fit together, from SAP to apps and reports. Habit of measuring before giving an opinion. Good communication to work with diverse teams, including support and business, and explain technical concepts to non-technical profiles. Analytical thinking, order to document and willingness to learn from senior architects and receive feedback.

Grupo Mariposa is a multinational food and beverage corporation founded in 1885, with operations in more than 14 countries and more than 15,000 employees. We have the largest beverage portfolio in the region and partnerships with global leaders such as PepsiCo and AB InBev. In recent years we have expanded globally and reorganized into four business units: apex (transformation), cbc (distribution), beliv (beverage innovation) and bia (food). We are looking for talents to enhance our growth strategy and bring joy and development throughout the organization. In this role, you will have the opportunity to lead data and AI architecture, designing scalable solutions that enable large-scale analytics and the operationalization of ML/AI models in production environments.

• Support the architecture team in the design of solutions on the Lakehouse platform in Azure and Databricks, following the team's reference architectures and standards.
• Design and review the integration patterns between the Lakehouse and the operational stores (MongoDB and Couchbase): publish pattern, purge strategies, indexes and write performance from the ETLs.
• Support in the data modeling of the platform: masters in silver, public views and RLS in gold with security by country, and document models for applications, considering multi-country and multi-tenant scenarios.
• Measure before deciding: use system tables and Unity Catalog lineage to analyze costs, usage, performance and impact before proposing architectural changes.
• Participate in production passes: review PRs, define criteria for QA and validate after the pass.
• Diagnose end-to-end incidents with support and business, from l

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