ML Ops Automation Engineer - Databricks, Snowflake, AWS

Aptonet; México; On-site; MXN 900,000 - 1,200,000; Full time

Job summary

Aptonet is seeking a skilled Data Engineer to support AI Enablement initiatives. You will build solutions in Databricks using Python, with preferred experience in Snowflake, Jenkins CI/CD, AWS, and DevOps.

The role focuses on automating ML lifecycles, model governance, and scalable data workflows. You will collaborate with data scientists and engineers to implement reusable libraries for authentication, logging, and reporting, and to automate environment provisioning for model development

Qualifications

• Bachelor’s degree in a related field and 5+ years of data engineering development experience.
• Proficiency with Python/Scala for data engineering and ML workflows.
• Experience with Snowflake, Databricks, and DevOps tooling (Jenkins, IaC).

Responsibilities

• Design, implement, and maintain automated workflows and ML model lifecycle infrastructure.
• Build robust CI/CD pipelines for ML models and ensure model versioning, monitoring, and governance.
• Develop data ingestion and scoring pipelines, and integrate data with APIs and web access.
• Collaborate with data scientists, actuarial, and engineering teams to deliver scalable systems.

Skills

Python

Scala

C#

Java

Linux/UNIX

Analytical skills

Data engineering

Education

Bachelor’s degree in Statistics, Computer Science, Data Engineering, Information Systems, or related field

Master’s degree in Statistics, Computer Science, Information Systems, Data Engineering, or related field

Tools

Snowflake

Databricks

Jenkins

Terraform

CloudFormation

AWS

Oracle

MS SQL Server

Job description

Aptonet is seeking a skilled Data Engineer to support AI Enablement initiatives. You will build solutions in Databricks using Python, with preferred experience in Snowflake, Jenkins CI/CD, AWS, and DevOps.

The role focuses on automating ML lifecycles, model governance, and scalable data workflows. You will collaborate with data scientists and engineers to implement reusable libraries for authentication, logging, and reporting, and to automate environment provisioning for model development