Remote Data & AI Engineer: Lakehouse & ML Ops

RevStar; Yuma (AZ); Remote; USD 150,000 - 190,000; Full time

Benefits offered by this job

Paid Time Off

Remote-First Working Environment

Comprehensive Health Coverage

401(k) Retirement Plan

Annual Learning & Development Stipend

Peer Mentorship & Coaching

Professional Growth Opportunities

Company Outings & VolunteerOpportuniti

Collaborative, Innovative Culture

Job summary

RevStar is seeking a Data & AI Engineer to build greenfield Lakehouse solutions at the cutting edge of AI and big data. You will design scalable pipelines, deploy production-grade AI models, and work with data architects and client leaders to turn complex data into actionable insights.

The role emphasizes ownership, self-mastery, and shared destiny, with a remote-first environment and multi-cloud deployments.

Qualifications

• Core Experience: 3+ years in cloud-native data engineering with 2+ years of hands-on Databricks, Spark, Delta Lake, MLflow.
• Technical Mastery: Python, SQL, Spark, CI/CD, and Infrastructure-as-Code (Terraform or Databricks CLI).
• Strong Differentiator: Databricks certification strongly preferred (Associate/Professional) or Databricks ML Professional.
• Consulting Mindset: Experience in fast-paced Agile/DevOps consulting environments with cloud-agnostic architectures.

Responsibilities

• Design, build, and optimize Databricks Lakehouse pipelines across multi-cloud environments.
• Operationalize AI models inside Databricks using MLflow with CI/CD and IaC tooling.
• Collaborate with client leadership to translate data requirements into scalable, production-ready solutions.

Skills

Databricks

Apache Spark

Delta Lake

MLflow

Python

SQL

CI/CD

Terraform

Databricks CLI

Databricks Certified Data Engineer

Job description

RevStar is seeking a Data & AI Engineer to build greenfield Lakehouse solutions at the cutting edge of AI and big data. You will design scalable pipelines, deploy production-grade AI models, and work with data architects and client leaders to turn complex data into actionable insights.

The role emphasizes ownership, self-mastery, and shared destiny, with a remote-first environment and multi-cloud deployments.