Lead Databricks Data & AI Solution Architect

Eliassen Group; United States; Remote; USD 138,000 - 145,000; Full time

Benefits offered by this job

Medical, Dental, Vision benefits

401(k) with company matching

Life insurance

Job summary

Eliassen Group is seeking a Senior Solution Architect for a remote Data & AI modernization initiative. You will own the architecture across Databricks platform modernization, governance, and AI-enabled solutions, guiding senior engineers and collaborating with security, data, and business stakeholders.

The role is hands-on and requires moving between enterprise architecture, platform design, and problem solving, with a focus on scalable, governed data products and AI readiness.

Qualifications

• Deep understanding of Databricks Lakeflow connect capabilities and AWS analytics and ingestion services.
• Extensive experience designing enterprise Databricks lakehouse architectures with Spark, Delta Lake, Lakeflow, and Unity Catalog.
• Experience designing enterprise data governance, lineage, security, and access-control frameworks including ABAC and RBAC.

Responsibilities

• Lead a Databricks Well-Architected assessment across platform architecture, observability, pipelines, consumption, data quality, security, governance, and cost.
• Establish architectural patterns supporting scalable data ingestion, transformation, analytics, AI, and agent-based solutions.
• Design and implement governance standards leveraging Databricks Unity Catalog and define access control policies.

Skills

Databricks Lakeflow

AWS analytics

Data governance

CI/CD

ABAC/RBAC security

Unified Catalog governance

Tools

Databricks Unity Catalog

Databricks Lakehouse

Spark/Delta Lake

MCP endpoints

Job description

Eliassen Group is seeking a Senior Solution Architect for a remote Data & AI modernization initiative. You will own the architecture across Databricks platform modernization, governance, and AI-enabled solutions, guiding senior engineers and collaborating with security, data, and business stakeholders.

The role is hands-on and requires moving between enterprise architecture, platform design, and problem solving, with a focus on scalable, governed data products and AI readiness.