Data & ai Engineer H/F

RevStar; New York (NY); Remote; USD 110,000 - 180,000; Full time

Benefits offered by this job

Comprehensive Health Coverage

401(k) Retirement Plan

Peer Mentorship & Coaching

Professional Growth Opportunities

Company Outings & Volunteer Activities

Job summary

RevStar is seeking a Data & AI Engineer to design, build, and optimize scalable ETL/ELT pipelines across multi-cloud environments. You will collaborate with data scientists and client leaders to operationalize AI models inside Databricks using MLflow and implement CI/CD pipelines with Terraform and Databricks CLI.

This remote-friendly role emphasizes production-grade data architectures and fast, impactful engineering work.

Qualifications

• 3+ years in cloud-native data engineering with 2+ years using Databricks, Spark, Delta Lake, and MLflow.
• High proficiency in Python, SQL, Spark frameworks, CI/CD and Infrastructure-as-Code (Terraform or Databricks CLI).
• Active Databricks Certification (Associate or Professional) strongly preferred; experience in Agile/DevOps consulting.

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines across multi-cloud environments (AWS, Azure, GCP).
• Collaborate with data scientists and client leaders to operationalize AI models in Databricks using MLflow.
• Implement CI/CD pipelines and IaC (Terraform, Databricks CLI) for production deployments.
• Translate data requirements into scalable data architectures and clear business outcomes.

Skills

Python

SQL

Apache Spark

MLflow

CI/CD

Terraform

Databricks CLI

Tools

Databricks

Delta Lake

MLflow

Job description

Build What Matters at RevStar

Position:

Data & AI EngineerReports To:

Product Manager/Engineering LeadLocation

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

Full-Time W2Ready 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.

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 architects 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.

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.