Data & AI Engineer: Lakehouse & MLOps Specialist (Remote)

RevStar Consulting Inc; Maine; Remote; USD 120,000 - 180,000; 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 Opportuni

Collaborative, Innovative Culture

Job summary

RevStar is seeking a Data & AI Engineer to build greenfield Lakehouse solutions, leveraging Databricks and multi-cloud architectures. You will turn complex data into scalable, production-ready AI models and collaborate with data scientists, architects, and client leaders in fast-paced engagements.

In this remote-friendly role, you’ll implement end-to-end pipelines, apply MLflow for model tracking, and contribute to governance and security standards while delivering tangible business impact.

Qualifications

• 3+ years cloud-native data engineering with 2+ years Databricks, Spark, Delta Lake, and MLflow.
• Proficiency in Python, SQL, Spark, CI/CD, and Infrastructure-as-Code (Terraform or Databricks CLI).
• Active Databricks Certified Data Engineer (Associate or Professional) or Databricks ML Professional preferred.
• Experience delivering cloud-agnostic architectures with strong client communication.

Responsibilities

• Databricks Lakehouse & Pipeline Engineering: design, build, and optimize scalable ETL/ELT pipelines across multi-clouds.
• Performance Tuning & MLOps Integration: tune Spark, deploy ML models with MLflow, and automate CI/CD deployments.
• Data Governance & Client Leadership: enforce security/compliance; translate data needs into business outcomes; document and hand off solutions.

Skills

Databricks + Spark + Delta Lake + MLflo

Python + SQL + CI/CD + IaC

Databricks Certification

Consulting mindset, Agile/DevOps

Tools

Databricks CLI

Terraform

Job description

RevStar is seeking a Data & AI Engineer to build greenfield Lakehouse solutions, leveraging Databricks and multi-cloud architectures. You will turn complex data into scalable, production-ready AI models and collaborate with data scientists, architects, and client leaders in fast-paced engagements.

In this remote-friendly role, you’ll implement end-to-end pipelines, apply MLflow for model tracking, and contribute to governance and security standards while delivering tangible business impact.