EDP Solution Architect

The EDP Solution Architect is a senior, hands-on contract role responsible for designing end-to-end data solutions across the Enterprise Data Platform (EDP). EDP is built fully on Google Cloud Platform and supports both the migration of workloads from our legacy on-premises EDW and the build-out of net-new enterprise data products across marketing, customer, and other business domains. The Solution Architect operates at the use-case and workstream level translating business needs into conceptual, logical, and physical data designs that span ingestion, transformation, and the consumption layer.

This role sits close to the build. The Solution Architect partners daily with Tech Leads, Data Engineers, Product Managers, Business Analysts, SMEs, and Quality Engineers to design solutions that are deliverable, performant, and trustworthy and aligns with the Platform Architecture team to ensure designs adopt established platform standards, patterns, and guardrails. Strong, hands-on Google Cloud Platform fluency is essential BigQuery, Dataflow, Cloud Composer, Dataform, and Cloud Storage alongside deep experience in data modeling, mapping, and solution design., Design end-to-end data solutions for assigned migration waves and net-new use cases covering ingestion, transformation, and consumption from conceptual through logical and physical models. Define source-to-target mappings and transformation designs, including handling of data types, nulls, defaults, slowly changing dimensions, and business rule logic. Make hands-on Google Cloud Platform service selection and design decisions across BigQuery, Dataflow, Cloud Composer, Dataform, and Cloud Storage balancing performance, cost, security, and operability. Design dimensional and analytics-ready data models (star schemas, fact / dimension structures) that align with downstream BI and consumption needs. Apply security, access, and least-privilege design principles at the dataset and domain level in line with platform standards. Partner closely with Tech Leads and Data Engineers providing hands-on design guidance, unblocking tradeoff decisions, and reviewing implementation against the agreed design. Engage with Product Managers, Business Analysts, and SMEs to translate business requirements into clear, executable solution designs and data product definitions. Partner with the EDP QA / QE Lead and Quality Engineers to ensure quality is designed in including validation hooks, reconciliation strategy, and data quality expectations baked into the solution from day one. Collaborate with the Platform Architecture team to adopt platform standards and patterns, surface gaps or exceptions, and contribute reusable patterns back from delivery learnings. Lead solution design reviews, document key design decisions and tradeoffs, and communicate clearly to both technical and non-technical stakeholders. Contribute pragmatically to AI / GenAI enablement on EDP where it strengthens solution outcomes for example, supporting metadata-driven workflows, AI-ready data product design, and consumption patterns for AI / data-agent use cases. Operate in a Scrum/ Kanban / Agile model using Jira and Confluence; deliver iterative, measurable outcomes.

7+ years of progressive experience in data engineering and solution architecture on enterprise data platforms, with significant hands-on delivery experience. Strong, hands-on experience with Google Cloud Platform data services BigQuery (modeling, optimization, cost / performance patterns), Dataflow, Cloud Composer, Dataform, and Cloud Storage. Demonstrated expertise across the full data management lifecycle conceptual, logical, and physical data modeling; source-to-target mapping; transformation design; and data product structure. Strong foundation in dimensional modeling and star schemas, metric definitions, and consumption-ready data structures. Strong SQL skills, including the ability to design and reason about complex queries and transformations on large data sets. Working knowledge of security and access design on Google Cloud Platform IAM, least-privilege, and domain / dataset-based access concepts. Demonstrated ability to operate across architecture and implementation defining a design, guiding engineers through it, and reviewing the build against intent. Strong collaboration and communication skills; able to explain tradeoffs and design decisions to both technical and non-technical stakeholders. Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline, or equivalent professional experience.

Preferred Qualifications Prior experience on a platform modernization or EDW-to-Google Cloud Platform migration program of comparable scale. Experience in retail / consumer / omni-channel domains (customer, product, inventory, orders, pricing, promotions, loyalty). Familiarity with semantic layer concepts, data catalog / metadata platforms, and governance workflows. Exposure to LLM-enabled or agentic tooling and patterns for AI-ready data products. Working proficiency in Python for prototyping and pipeline support. Google Cloud Platform certification, particularly Professional Data Engineer or Professional Cloud Architect.

Team & Culture Fit Pragmatic problem-solver who balances speed vs. durability, innovation vs. standardization, and incremental delivery vs. long-term platform fit. Collaborative and outcome-driven works shoulder-to-shoulder with engineers, product, BAs, and quality partners rather than designing from a distance. Strong ownership identifies gaps, proposes options, drives alignment and closure on design decisions. Comfortable with ambiguity and multi-wave delivery; able to manage design across multiple use cases and pipelines in parallel. Clear, concise communicator who tailors messaging from engineers to executives.