Data Solution Architect

Job Description: Data Solution Architect Job Summary Vertiv is building a modern, AI‑ready data ecosystem that powers analytics, domain data products, and digital applications. As part of this journey, we are seeking a Data Solution Architect who is highly hands‑on and execution‑focused, responsible for translating data architecture standards into working data solutions. This role owns solution‑level design and implementation across Snowflake, data products, APIs, and cloud integration. The Solution Architect focuses on designing, prototyping, and guiding real implementations alongside engineers and product teams. This would be a very hands-on solution oriented Data Architect role. Key Responsibilities Data Solution Architecture & Design Design end‑to‑end data solutions using Snowflake for analytics, domain data products, AI use cases and insights generation Translate business use cases into practical, implementable designs Create solution designs across: Ingestion Silver → Gold -> Data Product layers Output ports (views, APIs, feeds) Consumption patterns (Marketplace, BI, AI) Support and design Code Red use cases requiring Data Architecture for design and implementation Snowflake & Data Engineering Enablement Work hands‑on with Engineering team to: Define schemas, data models, and transformations Design performant SQL and ELT patterns Review pipelines, queries, and data models Guide use of Snowflake capabilities (dynamic tables, streams, tasks, secure views, data sharing) API‑First & Marketplace Integration Design API‑first access patterns for data products exposed through the Data Marketplace Partner with Full‑Stack Engineers to ensure: Clean separation between data logic and application logic Secure, scalable data access Define integration patterns between: Snowflake AWS services Marketplace backend APIs Cloud & Platform Integration Design data solutions that run on AWS‑hosted platforms Define integration patterns for: IAM / Okta / access control Event‑driven and batch data flows Ensure security, scalability, and operational robustness Data Quality, Metadata & AI Readiness Ensure solution designs embed: Data quality checks Metadata and lineage Observability and monitoring Work with the Principal Data Architect to ensure data products are AI‑ready (consistent, well‑modeled, governed) and use cases are architected and designed for scalability and defined data standards AI‑First Delivery Approach Actively leverage AI tools to: Accelerate solution design and prototyping Improve code quality and documentation Generate and validate SQL, APIs, and test cases Encourage AI‑assisted development practices across engineering teams Required Qualifications 5-7+ years of experience in data engineering, data modeling, solution architecture, or data platform roles Strong hands‑on expertise with Snowflake (SQL, data modeling, performance) Experience designing end‑to‑end data solutions, not just individual pipelines Strong understanding of: Data products and modern data architecture patterns Cloud platforms (AWS preferred) API‑first and microservices‑style integration Experience working closely with engineering teams in agile delivery models Strong documentation and communication skills (designs, trade‑offs, diagrams) Preferred Qualifications Experience enabling AI / Analytics use cases on data platforms leveraging Enterprise Data Prior experience with Snowflake, Data Marketplaces/catalogs, or self‑service analytics Experience in Manufacturing or Engineering domains Snowflake or cloud certifications. #LI-RB1