Senior Solution Architect – Databricks, Data & AI

Eliassen Group; United States; A distancia; USD 138.000 - 145.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Medical, Dental, Vision benefits

401(k) with company matching

Life insurance

Descripción de la vacante

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.

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Databricks Lakeflow

AWS analytics

Data governance

CI/CD

ABAC/RBAC security

Unified Catalog governance

Herramientas

Databricks Unity Catalog

Databricks Lakehouse

Spark/Delta Lake

MCP endpoints

Descripción del empleo

Remote

Our client is seeking a Senior Solution Architect to provide technical leadership for a large-scale Data & AI modernization initiative. This individual will own the overall architecture and technical direction across Databricks platform modernization, data engineering, governance, observability, semantic architecture, and AI/agent enablement. The Solution Architect will work closely with platform, data, security, business, and engineering stakeholders while providing technical leadership to a team of senior and staff-level Data & AI Engineers. This role is hands-on and requires the ability to move between enterprise architecture, Databricks platform design, governance, and technical problem solving.

We can facilitate w2 and corp-to-corp consultants. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $100.00 to $105.00/hr. w2

JN -112026-109352

Responsibilities:

• Lead a Databricks Well-Architected assessment across platform architecture, observability, pipelines, consumption, data quality, security, governance, and cost. Define target-state architecture and technical standards for the Data & AI platform. Identify architectural gaps, technical debt, platform risks, and remediation priorities.
• Establish architectural patterns supporting scalable data ingestion, transformation, analytics, AI, and agent-based solutions. Guide engineering teams in implementing standards and remediation priorities. Establish standards for development, test, production promotion, CI/CD, monitoring, and operational support.
• Design and implement governance standards leveraging Databricks Unity Catalog. Define least-privilege access models, attribute-based access control policies, data classification, tagging, and lineage standards. Establish monitoring for system health, jobs, pipelines, audit activity, data quality, and platform performance. Implement platform approaches for cost monitoring and optimization.
• Define data architecture standards for Bronze, Silver, and Gold medallion layers. Establish reusable patterns for source ingestion, transformation, data quality, lineage, and deployment. Architect configuration-driven onboarding frameworks using Databricks Lakeflow, Asset Bundles, YAML/control tables, and automated CI/CD. Guide development of conformed dimensions, shared business keys, and cross-domain data products.
• Define the architecture for an AI-ready Gold layer with certified, governed, documented data products. Design semantic and context layers using governed business definitions, metric views, KPIs, metadata, and business glossary information. Architect natural-language analytics using Databricks Genie. Define agent-ready interfaces using governed Unity Catalog functions, MCP endpoints, tracing, and evaluation.
• Provide architectural direction and technical mentorship to Data & AI Engineers. Partner with business SMEs and data owners to translate requirements into scalable technical solutions. Lead architecture and design reviews. Establish reusable engineering standards, reference architectures, runbooks, and implementation patterns. Participate in milestone and steering reviews.
• Deliver a secure, observable, governed, cost-aware, AI-ready Databricks architecture that can scale beyond a single use case. Produce assessment scorecards, remediation plans, platform standards, reusable data architecture patterns, and semantic and AI architecture assets. Enable operational readiness with monitoring, runbooks, documentation, and knowledge transfer.

Experience Requirements:

• Deep understanding of Databricks Lakeflow connect capabilities and AWS analytics and ingestion services.
• Extensive experience addressing ingestion challenges from unsupported sources by Lakeflow connect, including CDC handling and reconciliation techniques.
• Expertise with data quality libraries and configuration-based frameworks that plug DQ into ingestion pipelines.
• Extensive experience designing enterprise Databricks lakehouse architectures with Spark, Delta Lake, Lakeflow, and Unity Catalog.
• Strong experience with medallion architecture and Bronze/Silver/Gold data patterns.
• Experience designing enterprise data governance, lineage, security, and access-control frameworks including ABAC and RBAC, data classification, tagging, and least-privilege security.
• Experience designing production-grade data pipelines, reusable ingestion frameworks, observability, CI/CD, deployment automation, and production support.
• Experience designing semantic layers and governed enterprise data products, and architecting AI or GenAI solutions operating against governed enterprise data, including Databricks Genie and AI/BI.
• Experience with MCP and agent-based architectures, GenAI governance, tracing, and evaluation preferred.
• Strong communication skills and ability to work across engineering, security, architecture, and business teams.