At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D; and engineering services across all industries.

Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

YOUR ROLE:

This role is responsible for designing, building, maintaining, enhancing, and monitoring robust and scalable data pipelines that support Data & Analytics solutions, as well as data integration and migration between Swiss Re and external partners through APIs, SFTP, and other integration methods.

The role plays an important part in ensuring that high-quality, secure, accurate, and reliable data is made available to internal users and external partners across our client´s ecosystem, while supporting efficient, governed, and well-structured data flows.

Key Responsibilities

- Design, develop, and maintain end-to-end data pipelines supporting business and analytics requirements.
- Build scalable and reliable data ingestion, transformation, and delivery processes.
- Monitor pipeline executions and continuously optimize performance and resource utilization.
- Translate business and functional requirements into technical data specifications.
- Break down technical specifications into clear and actionable development tasks.
- Define and implement data quality rules, validations, and controls across data pipelines.
- Follow our client´s guidelines and governance processes during development, manipulating and sharing data.
- Ensure data consistency, completeness, accuracy, and traceability throughout the data lifecycle.

YOUR PROFILE:

- Bachelor Degree in Computer Sciences or equivalent
- 4+ years of experience in Data Engineering or related technical roles.




- Strong experience with SQL, Spark/Python , relational databases , and database procedures .
- Strong experience designing and developing ETL/ELT pipelines and complex data transformations.
- Experience with data modeling, data architecture, and large-scale data processing.
- Experience with APIs, SFTP , and enterprise data integration patterns .
- Experience with distributed systems and cloud platforms , preferably Microsoft Azure .
- Experience with monitoring, logging, troubleshooting, and production support of data pipelines.
- Experience working with Scrum/Agile development methodologies.
- Experience working and speaking in English with Developers or Stakeholders.

Nice-to-have (extra) skills:
- Experience with Palantir Foundry.
- Experience developing or integrating AI-driven applications and solutions.

WHAT YOU´LL LOVE: -Work on meaningful projects that use technology to solve real-world challenges.

-Exposure to top global companies working with Capgemini (145 of the Fortune 500 companies).

-Thrive in a diverse, respectful, and inclusive environment.

ABOUT CAPGEMINI:

Capgemini is an AI-powered general business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries.

We deliver end-to end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations.

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.

📌 Advanced Data Engineer - Remote in México
🏢 Capgemini Engineering
📍 México