Data Modeler

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.

Your Role

As a Data Modeler at Capgemini, you will play a key role in analyzing legacy data integration solutions, defining enterprise data models, and supporting modernization initiatives in cloud-based data platforms. You will work closely with Data Engineers, Architects, and Business Stakeholders to understand existing data transformation logic, develop source-to-target mappings, and ensure data quality throughout migration and modernization efforts.

This role requires strong SQL expertise, experience with SSIS reverse engineering, and a solid understanding of data modeling principles and best practices. You will serve as a critical bridge between legacy systems and modern Azure-based data platforms.

Responsibilities & Scope

• Analyze and interpret existing SSIS packages, workflows, and data transformation processes.
• Reverse engineer legacy ETL jobs to identify business rules, transformation logic, dependencies, and data flows.
• Document transformation processes, technical specifications, and data lineage in a clear and structured manner.
• Design and maintain conceptual, logical, and physical data models based on business and technical requirements.
• Apply industry-standard data modeling methodologies including:
• Third Normal Form (3NF)
• Star Schema
• Dimensional Modeling
• Develop comprehensive source-to-target mapping documents incorporating transformation logic, business rules, and lineage requirements.
• Collaborate with Enterprise Architects and Data Engineering teams to ensure alignment with target-state data architectures.
• Work closely with Data Engineers developing modern pipelines in Azure Databricks and cloud-based environments.
• Provide functional and technical guidance throughout the development lifecycle.
• Conduct data validation activities between legacy systems and new cloud platforms.
• Verify transformation accuracy and ensure data quality standards are consistently met.
• Identify, document, and support the resolution of data quality and reconciliation issues.
• Contribute to data governance, documentation, and metadata management initiatives.

Your Profile

• Analytical thinker – Able to understand complex legacy systems and translate technical logic into scalable data solutions.
• Data modeling expert – Strong understanding of relational and dimensional data modeling principles.
• Documentation-focused – Creates clear, detailed, and accurate technical documentation and mapping specifications.
• Collaborative partner – Effectively works with architects, engineers, analysts, and business stakeholders.
• Problem solver – Identifies data challenges, investigates root causes, and proposes practical solutions to improve data quality and consistency.

Technical Requirements

• 3–6 years of experience as a Data Modeler, Data Analyst, or related data-focused role.
• Strong proficiency in SQL, including:
• Complex queries
• Query optimization
• Data analysis and validation
• Hands-on experience with SSIS (SQL Server Integration Services).
• Proven ability to analyze and reverse engineer SSIS packages and ETL processes.
• Strong understanding of:
• Relational Data Modeling
• Third Normal Form (3NF)
• Star Schema Design
• Dimensional Modeling
• Experience creating:
• Source-to-Target Mapping Documents
• Technical Specifications
• Data Flow Documentation
• Data Lineage Artifacts
• Familiarity with:
• Azure Databricks
• Apache Spark concepts
• Modern Data Engineering pipelines
• Strong analytical, problem-solving, and communication skills.
• Experience collaborating with cross-functional technical teams.

Nice to Have

• Experience with:
• Azure Data Lake
• Azure SQL
• Delta Lake
• Understanding of:
• Data Governance
• Metadata Management
• Data Lineage Frameworks
• Experience working in Agile environments.
• Exposure to cloud migration and data modernization projects.
• Familiarity with enterprise-scale data warehouse architectures.

What you'll love

• Exposure to top global companies working with Capgemini (145 of the Fortune 500 companies)
• Tech solutions and projects driving societal impact and paving the way for a sustainable future
• Well-being hub and different wellbeing initiatives

Need to know

• Career Development in Spanish & English: Training, certifications, and mentorship programs available in both languages to support bilingual growth.
• Community Engagement: Participate in local volunteering initiatives, tech meetups, and cultural events that connect you with the Capgemini community.
• Opportunity to work on large-scale cloud transformation and data modernization initiatives leveraging Azure technologies and modern data platforms.

About Capgemini

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 are welcome and will be considered based on merit against the job and/or experience for the position.