Remote MLOps & Data Engineer (Databricks)

Jobgether; United States; Remote; USD 71,000 - 89,000; Full time

Benefits offered by this job

Fully remote work

Four weeks vacation

Health coverage

Telemedicine services

EAP

RRSP with employer matching

Internet expense reimbursement

Inclusive workplace

Job summary

Jobgether is seeking an experienced Data Engineer / MLOps Engineer to design and maintain scalable ML pipelines in a fully remote setup across Canada and support advertising data infrastructure. The role requires collaboration with data scientists and software engineers to productionize models and ensure reliable pipelines.

You will work with Python, Spark, and Databricks, implementing CI/CD across ML workflows and optimizing cloud resources.

Qualifications

• Experience in Data Engineering, MLOps, or DevOps with automation and distributed systems.
• Strong Python and Spark; Scala is a plus.
• Databricks expertise including Delta Lake and streaming.

Responsibilities

• Design and maintain MLOps pipelines with CI/CD for ML workflows.
• Develop scalable data processing using Spark to handle large datasets.
• Manage Databricks environments and optimize costs.
• Productionize ML models via scalable APIs and batch systems.
• Implement testing, monitoring, and alerting for reliability.
• Promote engineering best practices and environment reproducibility.
• Support advertising infrastructure with data feeds for autonomous platforms.
• Drive architectural improvements for performance and scalability.

Skills

Python

Apache Spark

Scala

English

French (asset)

Tools

GitHub Actions

Jenkins

Azure DevOps

GitLab CI

ArgoCD

Databricks

Delta Lake

Kubernetes

OpenShift

Job description

Jobgether is seeking an experienced Data Engineer / MLOps Engineer to design and maintain scalable ML pipelines in a fully remote setup across Canada and support advertising data infrastructure. The role requires collaboration with data scientists and software engineers to productionize models and ensure reliable pipelines.

You will work with Python, Spark, and Databricks, implementing CI/CD across ML workflows and optimizing cloud resources.