Data Platform Engineer

Title: Data Platform Engineer

Capgemini

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Rol

• Microsoft Azure Data Factory
• Data Fabric data engineering Description and Location
• Design and develop data pipelines and models using Microsoft Fabric and OneLake, with a strong focus on interoperability and performance using columnar formats like Parquet and efficient serialization formats like Protobuf.  
• Collaborate with cross-functional teams (Product Owners, Azure Solution Architects, Data & Software Engineers) to drive a Fabric-native data platform that integrates seamlessly with Power BI. 
• Enable modern data architecture patterns, including Lakehouse, near real-time streaming, schema evolution, and efficient serialization in messaging and APIs.  
• Maintain and automate scalable data pipelines, emphasizing performance, metadata consistency, and optimal use of storage formats such as Parquet within the Microsoft ecosystem.  
• Champion DevOps practices, implementing CI/CD pipelines (via Azure DevOps or GitLab Pipelines) and Infrastructure-as-Code for consistent, secure deployment of Fabric-based solutions.  
• Monitor and optimize platform performance using observability tools, ensuring health, reliability, and cost-efficiency.  
• Drive cloud migration and modernization efforts, guiding the transition to Microsoft Azure and Fabric, ensuring format and schema

Profile

• Microsoft Azure
• Microsoft Fabric
• OneLake
• Azure Data Factory (ADF)
• Data pipelines
• Data modeling
• Azure DevOps / GitLab Pipelines
• CI/CD
• Infrastructure
• Fully based on Microsoft Fabric
• Integrated with Power BI
• Optimized for analytics

What you’ll love

• Persona driven PVP proof points GloCal elements displaying PVP proof points
• Empowered Careers with Purpose

Work on meaningful projects that use technology to solve real-world

challenges.

Be part of a company that values sustainability, inclusion, and digital equity.

About Capgemini

Capgemini (Footer)

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

At Capgemini Mexico, we aim to attract the best talent and are committed to creating a diverse and inclusive work environment, so there is no discrimination based on race, sex, sexual orientation, gender identity or expression, or any other characteristic of a person. All applications welcome and will be considered based on merit against the job and/or experience for the position.

Job Description

Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets.

Job Description - Grade Specific

The involves leading and managing a team of data engineers, overseeing data engineering projects, ensuring technical excellence, and fostering collaboration with stakeholders. They play a critical role in driving the success of data engineering initiatives and ensuring the delivery of reliable and high quality data solutions to support the organizations data driven objectives.