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Cloud Data Engineer- ONSITE CDMX

ExperiencedNo visa sponsorship
Capgemini logo

at Capgemini

Consultancies

Posted 16 days ago

No clicks

**Cloud Data Engineer - Onsite CDMX** Develop and maintain cloud-based data pipelines, supporting analytics and business reporting. Build and enhance ETL/ELT processes using GCP services like BigQuery, Dataproc, and Cloud Composer. Ensure data quality through validation, testing, and troubleshooting. Optimize SQL queries and support performance improvements. Collaborate with Agile teams for feature deployment and platform enhancements. Minimum 4 years of experience in Data Engineering or related roles. Proficient in Python, PySpark, SQL, and cloud-based data processing environments. Familiarity with BigQuery, Dataproc, and Cloud Composer. Understanding of ETL/ELT processes, data validation, and transformation concepts. Join Capgemini Engineering, a global leader in engineering services, to work on innovative projects across various industries. Enjoy a diverse, inclusive work environment with continuous learning opportunities.

Compensation
Not specified

Currency: Not specified

City
Not specified
Country
Mexico

Full Job Description

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the worlds 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

  • Develop and maintain data pipelines that support analytics and business reporting solutions.
  • Build and enhance ETL/ELT processes using cloud-based data technologies.
  • Perform data validation, testing, and troubleshooting activities to ensure data quality and reliability.
  • Optimize SQL queries and support improvements in data processing performance.
  • Collaborate with Agile teams to deliver new features, deployments, and platform enhancements.

Your Profile

  • 4-5 years of experience in Data Engineering, Data Development, or related data-focused roles.
  • Hands-on experience with Python, PySpark, SQL, and cloud-based data processing environments.
  • Familiarity with BigQuery, Dataproc, and Cloud Composer, with a willingness to expand expertise in GCP services.
  • Understanding of ETL/ELT processes, data pipelines, data quality, and data transformation concepts.
  • Strong problem-solving skills, eagerness to learn, and ability to work effectively in collaborative Agile environments.

What you'll love

  • Contribute to building a better future for people, planet, and society.
  • Thrive in a diverse, respectful, and inclusive environment.
  • Access continuous learning through internal academies, certifications, and mentorship.
  • Active employee networks promoting diversity, equity and inclusion like OutFront, CapAbility or Women@Capgemini.
  • A culture anchored in our Fun and Team spirit values.

About Capgemini

Capgemini is an AI-powered global 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.

Cloud Data Engineer- ONSITE CDMX

Compensation

Not specified

City: Not specified

Country: Mexico

Capgemini logo
Consultancies

16 days ago

No clicks

at Capgemini

ExperiencedNo visa sponsorship

**Cloud Data Engineer - Onsite CDMX** Develop and maintain cloud-based data pipelines, supporting analytics and business reporting. Build and enhance ETL/ELT processes using GCP services like BigQuery, Dataproc, and Cloud Composer. Ensure data quality through validation, testing, and troubleshooting. Optimize SQL queries and support performance improvements. Collaborate with Agile teams for feature deployment and platform enhancements. Minimum 4 years of experience in Data Engineering or related roles. Proficient in Python, PySpark, SQL, and cloud-based data processing environments. Familiarity with BigQuery, Dataproc, and Cloud Composer. Understanding of ETL/ELT processes, data validation, and transformation concepts. Join Capgemini Engineering, a global leader in engineering services, to work on innovative projects across various industries. Enjoy a diverse, inclusive work environment with continuous learning opportunities.

Full Job Description

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the worlds 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

  • Develop and maintain data pipelines that support analytics and business reporting solutions.
  • Build and enhance ETL/ELT processes using cloud-based data technologies.
  • Perform data validation, testing, and troubleshooting activities to ensure data quality and reliability.
  • Optimize SQL queries and support improvements in data processing performance.
  • Collaborate with Agile teams to deliver new features, deployments, and platform enhancements.

Your Profile

  • 4-5 years of experience in Data Engineering, Data Development, or related data-focused roles.
  • Hands-on experience with Python, PySpark, SQL, and cloud-based data processing environments.
  • Familiarity with BigQuery, Dataproc, and Cloud Composer, with a willingness to expand expertise in GCP services.
  • Understanding of ETL/ELT processes, data pipelines, data quality, and data transformation concepts.
  • Strong problem-solving skills, eagerness to learn, and ability to work effectively in collaborative Agile environments.

What you'll love

  • Contribute to building a better future for people, planet, and society.
  • Thrive in a diverse, respectful, and inclusive environment.
  • Access continuous learning through internal academies, certifications, and mentorship.
  • Active employee networks promoting diversity, equity and inclusion like OutFront, CapAbility or Women@Capgemini.
  • A culture anchored in our Fun and Team spirit values.

About Capgemini

Capgemini is an AI-powered global 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.