Databricks Solution Architect (Data & AI)

EPAM Systems • New York, NY

3d

About The Position

EPAM is seeking a Databricks Solution Architect to join its Data & AI practice in North America. The role designs and delivers governed data, analytics, and AI platforms on Databricks for enterprise clients and contributes to pre-sales pursuits by shaping solutions, estimates, and proposals. The position involves collaborating with multinational teams on innovative projects within EPAM’s dynamic and inclusive culture, with opportunities to continue learning and growing.

Requirements

• At least 8 years of experience in data engineering, data architecture, or software development, including at least 3 years designing solutions on Databricks.
• Hands-on proficiency in Python and SQL.
• Deep knowledge of Apache Spark, Delta Lake, Lakeflow (Spark Declarative Pipelines and Jobs), Databricks SQL, and Unity Catalog.
• Experience with at least one major cloud platform (Azure, AWS, or GCP) and its data services, networking, and security model.
• Proven experience leading large, client-driven implementation projects, including pre-sales and proposal work.
• Experience with streaming and messaging tools such as Kafka, Event Hubs, Kinesis, or Flink.
• Knowledge of design patterns, CI/CD, infrastructure as code (Terraform), and Databricks Asset Bundles.
• Working knowledge of AI on Databricks, including Mosaic AI, Agent Bricks, and MLflow.
• Strong communication and consulting skills, with fluent English (B2+ or higher).
• Authorization to work in the US or Canada.

Nice To Haves

• Scala proficiency.
• Databricks Solution Architect Champion certification (noted as a big plus).
• Certifications such as Data Engineer Professional, Generative AI Engineer Associate, or Machine Learning Professional.

Responsibilities

• Design end-to-end Lakehouse architectures on Databricks across Azure, AWS, or GCP, covering ingestion, medallion modeling, serving, governance, and cost control.
• Lead discovery and architecture workshops with client executives and engineering teams, and clearly present proposed solutions and roadmaps.
• Partner with sales and the Databricks field team on pursuits by shaping solutions, answering RFPs, building proposals, estimating effort, and running proofs of concept.
• Define target architectures and migration paths from other solutions to Databricks.
• Architect governance with Unity Catalog, including access control, lineage, data sharing, and compliance with client security requirements.
• Design AI solutions, including RAG, agentic workflows, Model Serving, Vector Search, and MLflow-based LLMOps and MLOps.
• Guide delivery teams through build and go-live, and review, audit, and improve existing designs and system architectures.
• Run performance tuning, optimization, and FinOps reviews for Spark and Databricks SQL workloads.

What This Job Offers

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