Data & AI Engineer

# Data & AI Engineer (Databricks Specialist) ## About the Role RevStar is seeking a Data & AI Engineer (Databricks Specialist) to join its dedicated Data, ML, and AI practice. As an official Databricks Partner, RevStar builds greenfield Lakehouse solutions and production-ready AI and big data solutions for enterprise clients. In this role, you will work with data architects, data scientists, ML engineers, and client technology leaders to design scalable Lakehouse architectures, build production data pipelines, operationalize AI models, and deliver cloud-agnostic solutions across AWS, Azure, and GCP. ## Key Responsibilities Design, build, and optimize scalable ETL/ELT pipelines using Apache Spark and Delta Lake across AWS, Azure, and GCP. Develop Lakehouse architectures capable of processing 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 within Databricks. Use MLflow for model tracking, versioning, and deployment. Implement CI/CD pipelines and Infrastructure-as-Code using Terraform and Databricks CLI. Enforce enterprise data security, access controls, and compliance standards including GDPR, HIPAA, and SOC 2 within Unity Catalog and cloud environments. Collaborate with client technology leaders, product managers, and engineering teams to translate AI data requirements into business outcomes. Create clear technical documentation. Lead solution handoffs to client engineering teams at project completion. ## Required Qualifications 3+ years of cloud-native data engineering experience. 2+ years of dedicated, hands-on experience with Databricks, Apache Spark, Delta Lake, and MLflow. High proficiency in Python and SQL. Strong experience with Spark frameworks, CI/CD, and Infrastructure-as-Code. Experience with Terraform or Databricks CLI. Proven experience working in fast-paced Agile/DevOps consulting environments. Experience delivering cloud-agnostic architectures. Strong client communication skills. ## Preferred Qualifications Active Databricks Certified Data Engineer Associate or Professional certification. Databricks ML Professional certification. ## Skills & Competencies Databricks Apache Spark Delta Lake MLflow Python SQL ETL/ELT pipeline engineering Lakehouse architecture Cloud-native data engineering AWS, Azure, and GCP CI/CD Infrastructure-as-Code Terraform Databricks CLI Unity Catalog Data governance and security MLOps Agile/DevOps Client communication and technical documentation ## Education & Experience Education: No specific educational requirement is stated in the source. Experience: 3+ years of cloud-native data engineering. 2+ years of hands-on Databricks, Apache Spark, Delta Lake, and MLflow experience. Experience in Agile/DevOps consulting environments and cloud-agnostic architecture delivery. ## Work Arrangement & Schedule Remote US-based Eastern or Central Time Zone preferred Full-time W2 ## Compensation & Benefits Compensation: Not specified in the source. Benefits include: Paid time off Remote-first working environment Medical, dental, and vision coverage Company-sponsored 401(k) Annual learning and development stipend Peer mentorship and coaching Professional growth opportunities Exposure to AWS GenAI, data, and cloud technologies Company outings and volunteer opportunities

• Collaborative and innovative work environment

## Compliance / Additional Information RevStar is an Equal Opportunity Workplace and states that it celebrates and supports differences among employees, customers, and the community.