Senior Data Architect (Data & AI)

Worldwide | Sept. 1, 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 and over 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 over 15,000 employees. We have the largest beverage portfolio in the region and strategic partnerships with PepsiCo and AB InBev. We are organized into four business units: apex (processing), cbc (distribution), beliv (beverage innovation), and bia (food). We are looking for talented individuals to join our expansion and growth strategy, share our aspirations, and contribute their vision to achieve great results.

We are seeking a "Data Engineering Lead" to lead the corporate data platform in a multi-cloud environment, with a focus on Azure and support for 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 across multiple countries.

We are looking for a Senior Data Architect with strategic vision to lead the design of our data platform.
Your mission will be to build a foundation that enables not only data analysis at scale but also the efficient operationalization of data models, machine learning, and AI solutions. You must be proficient in Databricks and have proven experience deploying models into production and managing architectures that support advanced analytics. The ability to define strategies for data governance, MLOps, and cross-functional collaboration among teams is highly valued.

Requirements:

• More than 5 years of experience in Data Engineering, Data Architecture, or ML Engineering.
• Expert proficiency in Databricks (Unity Catalog, Delta Lake, MLflow).
• Advanced programming skills in PySpark and Python for data engineering.
• Solid experience with or integrations into databases (schema design, query optimization, and scalability).
• Knowledge of cloud environments (Azure/GCP).

Desirable:

• Experience with feature stores.
• Knowledge of orchestration tools (Airflow, Prefect, etc.).
• Experience with AI and ML architectures, including MLOps practices (training, versioning, deployment, and monitoring).
• Familiarity with deploying LLMs or generative AI.
• Databricks certifications (Data Engineer or ML Practitioner).

Grupo Mariposa is a multinational food and beverage corporation founded in 1885, with operations in more than 14 countries and over 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 seeking talented individuals to drive our growth strategy and foster 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.

• Design and implement hybrid, scalable data and AI architectures (Lakehouse) to support massive data ingestion and ML/AI workloads.
• Define and standardize data science workflows, ensuring an agile and robust model lifecycle (MLOps).
• Serve as a technical expert in Databricks (Unity Catalog, Delta Lake, MLflow), ensuring best practices for code and performance.
• Model and optimize NoSQL schemas for high-performance, low-latency applications.
• Collaborate closely with Data Engineers and Data Scientists to bridge the gap between prototyping and production deployment.
• Lead AI-driven architecture initiatives, including batch vs. real-time inference patterns and model scalability.

• Opportunity to work remotely.
• Collaborative and dynamic work environment.
• Continuous professional development and growth opportunities.

Databricks certifications and demonstrable experience leading AI projects in production environments are preferred. Ability to communicate technical results to non-technical stakeholders and to lead multidisciplinary teams. Results-oriented, with analytical thinking and a hands-on approach to solving complex data problems at scale.

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