Data Solution Architect

Vertiv • Westerville, OH

6h

About The Position

Vertiv is building a modern, AI-ready data ecosystem to support analytics, domain data products, and digital applications. The Data Solution Architect is a highly hands-on, execution-focused role responsible for turning data architecture standards into working data solutions. The role owns solution-level design and implementation across Snowflake, data products, APIs, and cloud integration, working alongside engineers and product teams to design, prototype, and guide real implementations.

The architect designs end-to-end solutions for analytics, AI use cases, and insights generation; enables engineering teams with Snowflake design and implementation guidance; defines API-first access patterns for marketplace data products; and designs integrations on AWS-hosted platforms. Solution designs are expected to address security, scalability, operational robustness, data quality, metadata, lineage, observability, monitoring, and AI readiness. The role also actively uses AI tools to accelerate design and prototyping, improve code and documentation, and generate and validate SQL, APIs, and test cases.

Requirements

• 5–7+ years of experience in data engineering, data modeling, solution architecture, or data platform roles.
• Strong hands-on expertise with Snowflake, including SQL, data modeling, and performance.
• Experience designing end-to-end data solutions, not just individual pipelines.
• Strong understanding of data products and modern data architecture patterns.
• Strong understanding of cloud platforms; AWS is preferred.
• Strong understanding of API-first and microservices-style integration.
• Experience working closely with engineering teams in agile delivery models.
• Strong documentation and communication skills, including designs, trade-offs, and diagrams.

Nice To Haves

• Experience enabling AI or analytics use cases on data platforms leveraging enterprise data.
• Prior experience with Snowflake, Data Marketplaces or catalogs, or self-service analytics.
• Experience in manufacturing or engineering domains.
• Snowflake or cloud certifications.

Responsibilities

• Design end-to-end Snowflake data solutions for analytics, domain data products, AI use cases, and insights generation.
• Translate business use cases into practical, implementable designs.
• Create solution designs for ingestion, Silver-to-Gold and data product layers, output ports such as views, APIs, and feeds, and consumption through marketplaces, BI, and AI.
• Support and design Code Red use cases requiring data architecture for design and implementation.
• Work with engineering teams to define schemas, data models, and transformations; design performant SQL and ELT patterns; and review pipelines, queries, and data models.
• Guide use of Snowflake capabilities, including dynamic tables, streams, tasks, secure views, and data sharing.
• Design API-first access patterns for data products exposed through the Data Marketplace.
• Partner with full-stack engineers to establish clear separation between data and application logic and provide secure, scalable data access.
• Define integration patterns between Snowflake, AWS services, and Marketplace backend APIs.
• Design data solutions for AWS-hosted platforms, including IAM, Okta, access control, and event-driven and batch data flows.
• Ensure solutions are secure, scalable, and operationally robust.
• Embed data quality checks, metadata and lineage, observability, and monitoring into solution designs.
• Work with the Principal Data Architect to ensure data products are consistent, well-modeled, governed, AI-ready, scalable, and aligned with defined data standards.
• Use AI tools to accelerate solution design and prototyping, improve code quality and documentation, and generate and validate SQL, APIs, and test cases.
• Encourage AI-assisted development practices across engineering teams.

What This Job Offers

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