Data & AI Engineer

RevStar

1d • Remote

About The Position

RevStar is launching a dedicated, cloud-agnostic Data, ML, and AI practice as an innovation shop and official Databricks Partner. The Data & AI Engineer will build greenfield Lakehouse solutions and production AI for clients, working directly with data architects, scientists, and client leaders to turn complex data into scalable, production-ready AI models. The role focuses on delivering enterprise solutions in fast-paced execution cycles and emphasizes self-mastery, ownership, and shared destiny.

The engineer will design and optimize Lakehouse architectures and data pipelines across multi-cloud environments, operationalize AI models in Databricks, and establish production-grade deployment practices. The role also includes enforcing data governance and compliance, collaborating with client teams to connect technical requirements to business outcomes, and documenting solutions and handing them off to client engineering teams.

Requirements

• At least 3 years of cloud-native data engineering experience.
• At least 2 years of dedicated, hands-on experience with Databricks, Apache Spark, Delta Lake, and MLflow.
• High proficiency in Python, SQL, Spark frameworks, CI/CD, and Infrastructure-as-Code using Terraform or Databricks CLI.
• Proven track record in fast-paced Agile/DevOps consulting environments.
• Experience delivering cloud-agnostic architectures and communicating effectively with clients.

Nice To Haves

• Active Databricks Certified Data Engineer Associate or Professional certification, or Databricks ML Professional certification; strongly preferred.

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines using Apache Spark and Delta Lake across AWS, Azure, and GCP.
• Implement Lakehouse architectures that process structured and unstructured data at enterprise scale.
• Automate data ingestion, storage, and feature-engineering workflows for analytics and real-time AI workloads.
• Tune Spark jobs for low latency, high throughput, and cloud cost efficiency.
• Partner with ML engineers and data scientists to operationalize AI models in Databricks using MLflow for tracking, versioning, and deployment.
• Implement CI/CD pipelines and Infrastructure-as-Code using Terraform and Databricks CLI for automated, production-grade deployments.
• Enforce enterprise data security, access controls, and compliance standards in Unity Catalog and cloud environments.
• Collaborate with client technology leaders, product managers, and engineering teams to translate AI data requirements into business outcomes.
• Write technical documentation and lead solution handoffs to client engineering teams.

Benefits

• Paid time off.
• Remote-first working environment.
• Medical, dental, and vision coverage.
• Company-sponsored 401(k) plan.
• Annual learning and development stipend for conferences, certifications, or courses.
• Peer mentorship and coaching.
• Professional growth opportunities and exposure to AWS GenAI, data, and cloud technologies across diverse industries.
• Company outings and volunteer opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed