Databricks Lakehouse Engineer — AI/ML Pipelines (Remote)

RevStar; Maine; Remote; USD 120,000 - 170,000; 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 & Volunteer Opportunit

Job summary

RevStar is seeking an Data & AI Engineer to design and deploy greenfield Lakehouse solutions interfacing with data architects, scientists, and client leaders. You will help build scalable pipelines, production-grade AI models, and robust data governance across multi-cloud environments.

You will collaborate with ML engineers, data scientists, and product leaders to turn complex data into measurable business outcomes, while maintaining high standards of security and reliability in a remote-first

Qualifications

• 3+ years in cloud-native data engineering with Databricks, Spark, Delta Lake, and MLflow experience (2+ years hands-on).
• Proficiency in Python, SQL, Spark frameworks, CI/CD, and Terraform/Databricks CLI.
• Databricks certification strongly preferred; experience delivering cloud-agnostic architectures.

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines across multi-cloud environments.
• Operationalize AI models inside Databricks using MLflow; implement CI/CD and IaC for production deployments.
• Collaborate with clients and engineers to translate data requirements into production-ready solutions.

Skills

Python

SQL

Spark

CI/CD

Terraform

Databricks

MLflow

Tools

Databricks

Apache Spark

Delta Lake

MLflow

AWS

Azure

GCP

Job description

RevStar is seeking an Data & AI Engineer to design and deploy greenfield Lakehouse solutions interfacing with data architects, scientists, and client leaders. You will help build scalable pipelines, production-grade AI models, and robust data governance across multi-cloud environments.

You will collaborate with ML engineers, data scientists, and product leaders to turn complex data into measurable business outcomes, while maintaining high standards of security and reliability in a remote-first