Data & AI Engineer - WFH

About the Role

RevStar is seeking a Data & AI Engineer to design and build greenfield Lakehouse solutions and production-ready AI systems. As an official Databricks Partner, RevStar is establishing a cloud-agnostic Data, ML, and AI practice focused on delivering scalable enterprise solutions.

In this role, you will work directly with data architects, data scientists, and client leaders to turn complex data requirements into production-ready AI models and scalable data solutions. You will report to the Product Manager/Engineering Lead.

The team operates around three core principles: Self-Mastery, through continuous improvement and clear communication; Ownership, by taking responsibility for outcomes; and Shared Destiny, by working together toward shared success.

Key Responsibilities

Databricks Lakehouse & Pipeline Engineering

• Design, build, and optimize scalable ETL/ELT pipelines using Apache Spark and Delta Lake across AWS, Azure, and GCP.
• Develop Lakehouse architectures that process structured and unstructured data at enterprise scale.
• Automate data ingestion, storage, and feature engineering workflows to support analytics and real-time AI workloads.

Performance Tuning & MLOps Integration

• Optimize Spark jobs for low latency, high throughput, and cloud cost-efficiency.
• Work with ML engineers and data scientists to operationalize AI models in Databricks using MLflow for tracking, versioning, and deployment.
• Build CI/CD pipelines and Infrastructure-as-Code solutions using Terraform and Databricks CLI to support automated, production-grade deployments.

Data Governance & Client Leadership

• Implement enterprise data security, access controls, and compliance standards, including GDPR, HIPAA, and SOC 2, across Unity Catalog and cloud environments.
• Collaborate with client technology leaders, product managers, and engineering teams to translate AI data requirements into business outcomes.
• Prepare technical documentation and lead solution handoffs to client engineering teams upon project completion.

Required Qualifications

• At least 3 years of experience in cloud-native data engineering.
• At least 2 years of dedicated, hands-on experience with Databricks, Apache Spark, Delta Lake, and MLflow.
• Strong proficiency in Python, SQL, and Spark frameworks.
• Experience with CI/CD and Infrastructure-as-Code tools such as Terraform or Databricks CLI.
• Experience working in fast-paced Agile/DevOps consulting environments.
• Ability to deliver cloud-agnostic architectures and communicate effectively with clients.

Preferred Qualifications

• Active Databricks Certified Data Engineer (Associate or Professional) certification or Databricks ML Professional certification.

Location & Employment Type

Remote within the following states: Arizona, District of Columbia, Florida, Georgia, Iowa, Illinois, Maine, New York, New Jersey, South Carolina, Texas, and Virginia.

Full-time W-2 employment.

Benefits

• Paid time off.
• Remote-first working environment.
• Medical, dental, and vision coverage.
• Company-sponsored 401(k) retirement plan.
• Annual learning and development stipend for conferences, certifications, or courses.
• Peer mentorship and coaching from experienced engineers, product managers, and architects.
• Professional growth opportunities involving AWS GenAI, data, and cloud technologies across diverse industries.
• Company outings and volunteer opportunities.
• Collaborative and innovative work culture.

Equal Opportunity Employment

RevStar is an equal opportunity workplace. The company celebrates and supports differences among employees, customers, and the community.

Reasonable Accommodations

RevStar is committed to providing access, equal opportunity, and reasonable accommodations for individuals with disabilities across employment, services, programs, and activities. To request an accommodation, contact HR.

E-Verify

RevStar participates in E-Verify to confirm work authorization for all newly hired U.S. employees. This process applies only to direct W-2 hires and does not apply to independent contractor roles.