Databricks Solution Architect (Data & AI)

Requirements:

• 8+ years of experience in data engineering, data architecture, or software development, including 3+ years designing Databricks solutions
• Hands-on proficiency in Python and SQL; Scala is a plus
• 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 Google Cloud Platform), including 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
• Databricks Solution Architect Champion certification is a significant plus; certifications such as Data Engineer Professional, Generative AI Engineer Associate, or Machine Learning Professional are also welcome

Responsibilities:

• Design end-to-end Databricks Lakehouse architectures across Azure, AWS, or Google Cloud Platform, covering data ingestion, medallion modeling, serving, governance, and cost control
• Lead discovery and architecture workshops with client executives and engineering teams, and present proposed solutions and roadmaps
• Partner with sales and the Databricks field team on pursuits by shaping solutions, responding to RFPs, developing proposals, estimating effort, and running proofs of concept
• Define target architectures and migration paths from other platforms to Databricks
• Architect governance with Unity Catalog, including access control, lineage, data sharing, and alignment 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
• Conduct performance tuning, optimization, and FinOps reviews for Spark and Databricks SQL workloads

Technologies:

• AI
• AWS
• Architect
• Azure
• CI/CD
• Cloud
• Databricks
• Flink
• Kafka
• Machine Learning
• MLflow
• MLOps
• Model Serving
• Python
• RAG
• SQL
• Scala
• Security
• Spark
• Terraform
• Unity
• GameDev

More

We are seeking a Databricks Solution Architect to join EPAMs Data & AI practice in North America. EPAM is a global provider of digital platform engineering and development services. We aim to make a positive impact for our customers, employees, and communities, and offer a dynamic, inclusive culture where you can collaborate with multinational teams on innovative projects while continuing to learn and grow.

last updated 43 week of 2026