Senior DevOps Engineer - Data Platform & Fleet Analytics

Intel

Región Centro

On-site

MXN 700,000 - 1,100,000

Full time

14 days+

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Job summary

Intel Contract Employee in Guadalajara is seeking a Senior DevOps Engineer to develop and scale data platform software for fleet telemetry and health analytics. You will collaborate with software architects, validation teams, data scientists, and customer engineering to deliver scalable solutions on Azure and Kubernetes.

The role emphasizes Python-based backend services, CI/CD pipelines with Jenkins, and SQL data processing.

Qualifications

Bachelor's Degree in Computer Science, Computer Engineering, Electrical Engineering, Electronics Engineering, Data Engineering, Data Science, or related field with 7+ years of relevant experience.
Master's Degree in the same fields with 5+ years of relevant experience.
Advanced Python programming skills.
Experience deploying applications on Kubernetes (K8s).
Experience creating and maintaining CI/CD pipelines using Jenkins.
Knowledge of relational and non-relational databases.
Writing complex and optimized SQL queries.
Working with structured, semi-structured, and unstructured datasets.
Git, GitHub, and pull request workflows.
Microsoft Azure or similar cloud services.
Distributed computing frameworks such as Spark or Dask.
Debugging and automated tests development.
Docker and containerized development.
Advanced English level.
Must have unrestricted, permanent right to work in Mexico.

Responsibilities

Develop and maintain backend components for data platform infrastructure.
Work on data extraction, processing, and analysis of telemetry and health data.
Design scalable data processing pipelines using distributed frameworks.
Build analytics solutions for telemetry, reliability, and quality monitoring.
Perform SQL queries against cloud-hosted databases and optimize them.
Create and maintain data processing pipelines feeding data marts and analytics platforms.
Develop Python-based backend services and reporting tools.
Design dashboards and visualizations for engineering and customers.
Deploy and optimize services on Kubernetes-based infrastructure.
Create CI/CD pipelines using Jenkins and modern DevOps practices.
Collaborate with Azure cloud services for scalable data solutions.
Participate in release planning and operational readiness reviews.
Identify and resolve issues throughout the development lifecycle.