Data & ai Engineer H/F

RevStar; Williamstown (NJ); Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Remote-First

Health Coverage

401(k) Retirement Plan

Mentorship & Coaching

Professional Growth Opportunities

Company Outings & Volunteer

Job summary

RevStar is seeking a Data & AI Engineer to design greenfield Lakehouse solutions and production-grade AI models. You will work with data architects, scientists, and client leaders to turn complex data into scalable AI solutions.

Responsibilities include building ETL/ELT pipelines across multi-cloud environments, optimizing Spark workloads, and integrating MLOps with MLflow. You will contribute to data governance and production deployments, with emphasis on secure, scalable architectures.

Qualifications

• 3+ years in cloud-native data engineering with Databricks/Spark/Delta Lake.
• 2+ years hands-on Databricks, Spark, Delta Lake, MLflow experience.
• Proficiency in Python, SQL, Spark, CI/CD, and Infrastructure-as-Code (Terraform or Databricks CLI).
• Active Databricks certification is highly preferred.

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines across multi-cloud environments.
• Operationalize AI models inside Databricks using MLflow and maintain CI/CD pipelines.
• Enforce data governance and collaborate with clients to translate AI data needs into outcomes.
• Document solutions and lead handoffs to client engineering teams.

Skills

Python

SQL

Apache Spark

Delta Lake

MLflow

CI/CD

Terraform

Databricks CLI

Tools

Databricks

MLflow

Job description

Build What Matters at RevStar Position: Data & AI Engineer

Reports To: Product Manager/Engineering Lead

Location : Remote (AZ, DC, FL, GA, IA, IL, ME, NY, NJ, SC, TX, VA)

Employment Type: Full-Time W2

Ready to build greenfield Lakehouse solutions at the bleeding edge of AI and big data?

RevStar is an innovation shop and official Databricks Partner launching a dedicated, cloud-agnostic Data, ML, and AI practice. Tired of spending months in endless corporate approval loops only to build AI concepts that never reach production? We turn modern Lakehouse architectures and production AI into live, scalable enterprise solutions in fast-paced execution cycles. We build fast, cut bureaucratic red tape, and ship production-ready solutions for client founders and tech leaders who value real engineering impact. In this role, you will work directly with data architects, scientists, and client leaders to turn complex data into scalable, production-ready AI models.

Databricks Lakehouse & Pipeline Engineering

Design, build, and optimize scalable ETL/ELT pipelines using Apache Spark and Delta Lake across multi-cloud environments (AWS, Azure, GCP). Implement robust Lakehouse architectures that seamlessly process both structured and unstructured data at enterprise scale. Automate data ingestion, storage, and feature engineering workflows to support downstream analytics and real-time AI workloads.

Performance Tuning & MLOps Integration

Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and data scientists to operationalize AI models inside Databricks using MLflow for tracking, versioning, and deployment. Implement robust CI/CD pipelines and Infrastructure-as-Code (Terraform, Databricks CLI) to establish automated, production-grade deployments.

Data Governance & Client Leadership

Enforce enterprise data security, access controls, and compliance standards (GDPR, HIPAA, SOC 2) within Unity Catalog and cloud ecosystems. Collaborate directly with client tech leaders, product managers, and engineering teams to translate complex AI data requirements into clear business outcomes. Author clean technical documentation and lead seamless solution handoffs to client engineering teams upon project completion.

Core Experience

3+ years in cloud-native data engineering with 2+ years of dedicated, hands-on Databricks, Apache Spark, Delta Lake, and MLflow experience.

High proficiency in Python, SQL, Spark frameworks, CI/CD, and Infrastructure-as-Code (Terraform or Databricks CLI).

Strong Differentiator

Active Databricks Certified Data Engineer (Associate or Professional) or Databricks ML Professional certification is strongly preferred and will set your application apart.

Proven track record

Operating in fast-paced Agile/DevOps consulting environments, delivering cloud-agnostic architectures with exceptional client communication.

Benefits & Working Environment

• Remote-First Working Environment – Collaborate from anywhere while staying connected with our global team.
• Comprehensive Health Coverage – Medical, Dental, Vision
• 401(k) Retirement Plan – Plan for your future with access to a company-sponsored 401(k) program.
• Peer Mentorship & Coaching – Learn from experienced engineers, product managers, and architect to accelerate your growth.
• Professional Growth Opportunities – Exposure to cutting-edge AWS GenAI, data, and cloud technologies across diverse industries.
• Company Outings & Volunteer Opportunities – Build relationships and give back to the community.

EO/EEO Statement

At RevStar, we don’t just accept differences — we celebrate them, we support them, and we thrive on them for the benefit of our employees, our customers, and our community. RevStar is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities.

This process applies strictly to direct W-2 hires and is not applicable to independent contractor roles.