Capgemini

Azure Data Engineer

Capgemini · Aguascalientes City, Aguascalientes, Mexico

IT Services and IT Consulting · 10,001+ employees

20 h ago
Mid (2-5 yrs) Full-time Mexico
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About the role

Design and implement data pipelines and ETL workflows using Azure tools while optimizing data storage for performance and cost. Collaborate with cross-functional teams to ensure data security, compliance, and governance across all platforms.

What they look for

Azure Data Factory Azure Databricks Azure Blob Storage SQL Python Spark Data modeling Data warehousing Big data technologies CI/CD DevOps Git Agile Scrum Problem-solving Communication

Requirements

Requires expertise in SQL, Python, Spark, and Azure data technologies along with experience in data modeling and warehousing. Candidates should possess strong analytical skills and familiarity with DevOps practices and Agile methodologies.

Benefits

Continuous learning Internal academies Certifications Mentorship Digital learning platforms

Full description

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.

Your Role

  • Design and implement data pipelines and ETL workflows using Azure Data Factory, Databricks, and related tools.
  • Optimize data storage and retrieval for performance and cost efficiency.
  • Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality data solutions.
  • Ensure data security, compliance, and governance across all platforms.
  • Monitor and troubleshoot data workflows to ensure reliability and accuracy.
  • Work in Agile/Scrum teams, participate in sprint planning, and collaborate with cross-functional teams.

Your Profile

  • Azure Data Factory
  • Azure Databricks
  • Azure Blob Storage
  • Expertise in SQL, Python, and Spark.
  • Experience with data modeling, data warehousing, and big data technologies.
  • Familiarity with CI/CD, DevOps practices, and Git.
  • Strong analytical and problem-solving abilities.
  • Excellent communication skills for technical and non-technical stakeholders.
  • Ability to work independently and mentor junior developers.

What you’ll love

Empowered Careers with Purpose: Work on meaningful projects that use technology to solve real-world challenges.

Growth and Learning at Every Step: Access continuous learning through internal academies, certifications and mentorship.

Own your growth: Open access to digital learning platforms

About Capgemini

Capgemini (Footer)

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-toend 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.

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 primary focus is to help organizations design, develop, and optimize their data infrastructure and systems. They help organizations enhance data processes, and leverage data effectively to drive business outcomes.