Job description

We are seeking a Databricks Solution Architect to join EPAM's Data & AI practice in North America. You will design and deliver governed data, analytics, and AI platforms on Databricks for enterprise clients, and you will join pre-sales pursuits to shape solutions, estimates, and proposals. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture, and you will collaborate with multinational teams on innovative projects while continuing to learn and grow. Req.#1112994925 Responsibilities: • Design end to end Lakehouse architectures on Databricks (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 present proposed solutions and roadmaps clearly • Partner with sales and the Databricks field team on pursuits: shape solutions, answer RFPs, build proposals, estimate effort, and run POCs • 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 Requirements: • 8+ years of experience in data engineering, data architecture, or software development, including 3+ years designing solutions on Databricks • 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 (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 (Mosaic AI, Agent Bricks, MLflow) • Strong communication and consulting skills, with fluent English (B2+ or higher) • Authorization to work in the US or Canada Nice to have: • Databricks Solution Architect Champion certification (a big plus), plus certifications such as Data Engineer Professional, Generative AI Engineer Associate, or Machine Learning Professional

Requirements

Must-haves

Req.#1112994925
Design end to end Lakehouse architectures on Databricks (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 present proposed solutions and roadmaps clearly
Partner with sales and the Databricks field team on pursuits: shape solutions, answer RFPs, build proposals, estimate effort, and run POCs
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
8+ years of experience in data engineering, data architecture, or software development, including 3+ years designing solutions on Databricks
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 (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 (Mosaic AI, Agent Bricks, MLflow)
Strong communication and consulting skills, with fluent English (B2+ or higher)
Authorization to work in the US or Canada

Nice-to-haves

Hands-on proficiency in Python and SQL; Scala is a plus
Databricks Solution Architect Champion certification (a big plus), plus certifications such as Data Engineer Professional, Generative AI Engineer Associate, or Machine Learning Professional

Application prep

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Keywords to mirror

aiazureawsgcpgosqlpythonci/cdmachine learning

Platform: epam
Effort: medium