Machine Learning Opps Engineer (Remoto en Mexico)

Guadalajara, JAL, MX

Capgemini

A global leader in consulting, technology services and digital transformation, we offer an array of integrated services combining technology with deep sector expertise.

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México, Remoto

Are you passionate about data and machine learning? Do you have expertise in Unity Catalog and Feature Store in Databricks? If so, Capgemini Engineering is looking for you to join our team and help us build and maintain a solid foundation for our data and machine learning workflows.



YOUR CONTRIBUTION: 

  • Organize and Secure Data: Set up and manage Unity Catalog in Databricks to organize and secure data access across teams.
  • Support ML Models: Design and operationalize Feature Stores to support machine learning models in production.
  • Build Data Pipelines: Create efficient data pipelines to process and serve features to ML workflows.
  • Collaborate Across Teams: Work with teams using Databricks, Azure Cosmos DB, and other Azure tools to integrate data solutions.
  • Optimize Performance: Monitor and optimize the performance of pipelines and feature stores.

 

 

 

YOUR PROFILE: 

- Bachelor's degree in Computer Science, Information Technology, or related field.

- Strong communication skills, with fluency in English.

- Minimum of 8 years' experience with the following: 

  • Unity Catalog Expertise: Strong experience with Unity Catalog in Databricks for managing data assets and access control.
  • Feature Store Experience: Hands-on experience with Databricks Feature Store or similar solutions.
  • ETL Pipelines: Knowledge of building and maintaining scalable ETL pipelines in Databricks.
  • Azure Tools: Familiarity with Azure tools like Azure Cosmos DB and ACR.
  • ML Workflows: Understanding of machine learning workflows and how feature stores fit into the pipeline.
  • Problem-Solving: Strong problem-solving skills and a collaborative mindset.
  • Programming Skills: Proficiency in Java (specifically Java APIM), Python, and Spark for data engineering tasks.
  • Monitoring Tools: Experience with monitoring tools like Splunk or Datadog to ensure system reliability.
  • Container Management: Familiarity with AKS for deploying and managing containers

 

 

 

WHAT YOU’LL LOVE ABOUT WORKING HERE?

  • Capgemini Employer Promise: Learning + Flexibility + Team Spirit + Inclusion + Innovation.
  • Work from home: fully remote position.
  • Get competitive benefits above the law.
  • Build your future within a worldwide leader in ER&D projects.
  • Feel free to grow within different industries and choose your career path.
  • Be part of a great family of Engineers, and people all over Mexico and the world.
     

Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 300,000 team members in nearly 50 countries. With its strong 50-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms.

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.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Azure Computer Science Cosmos DB Databricks Data pipelines Engineering ETL Java Machine Learning ML models Pipelines Python Spark Splunk

Perks/benefits: Career development

Regions: Remote/Anywhere North America
Country: Mexico

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