Remote Data & AI Engineer - Lakehouse & ML on Databricks

RevStar; Idaho Falls (ID); Remote; USD 130,000 - 180,000; Full time

Benefits offered by this job

Remote-first working environment

Comprehensive health coverage

Mentorship & coaching

Professional growth opportunities

Company outings & volunteer work

Job summary

RevStar is hiring a Data & AI Engineer to design and deploy scalable Lakehouse pipelines across AWS, Azure, and GCP. You will work closely with data architects, scientists, and client leaders to transform complex data into production-ready AI models.

You will leverage Databricks, Delta Lake, and MLflow, implement robust CI/CD, and apply Terraform & Databricks CLI for automated deployments in a fast-paced, remote-first environment.

Qualifications

• 3+ years in cloud-native data engineering with 2+ years on Databricks, Spark, Delta Lake and MLflow.
• High proficiency in Python, SQL, Spark frameworks, CI/CD, and Infrastructure-as-Code (Terraform or Databricks CLI).
• Active Databricks Certified Data Engineer or Databricks ML Professional certification preferred.
• Experience in Agile/DevOps consulting; cloud-agnostic architectures; strong client communication.

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines across multi-cloud environments.
• Implement CI/CD pipelines and IaC to enable production-grade deployments.
• Collaborate with data scientists and client leaders to deliver production-ready AI models.
• Translate complex data requirements into clear business outcomes and docs.

Skills

Python

SQL

Spark frameworks

CI/CD

Infrastructure-as-Code

Tools

Databricks CLI

Terraform

MLflow

Delta Lake

Databricks Platform

Job description

RevStar is hiring a Data & AI Engineer to design and deploy scalable Lakehouse pipelines across AWS, Azure, and GCP. You will work closely with data architects, scientists, and client leaders to transform complex data into production-ready AI models.

You will leverage Databricks, Delta Lake, and MLflow, implement robust CI/CD, and apply Terraform & Databricks CLI for automated deployments in a fast-paced, remote-first environment.