Lead Solutions Architect with Google Cloud Platform and GenAI

Retail domain client experience is required.

Looking for an enterprise Data Platform Solutions Architect with Google Cloud Platform experience.

Job Summary:

The EDP Solution Architect is a senior, hands on role responsible for designing end-to-end data solutions across an Enterprise Data Platform (EDP). The platform is built on Google Cloud Platform (Google Cloud Platform) and supports both the migration of workloads from a legacy on premises Enterprise Data Warehouse (EDW) and the development of new enterprise data products across multiple business domains.

This role operates at the use case and workstream level translating business needs into conceptual, logical, and physical data designs spanning ingestion, transformation, and consumption layers. The architect partners closely with Tech Leads, Data Engineers, Product Managers, Business Analysts, SMEs, and Quality Engineers to ensure solutions are performant, scalable, and aligned with platform standards.

Strong, hands on Google Cloud Platform experience is essential including BigQuery, Dataflow, Cloud Composer, Dataform, and Cloud Storage along with deep expertise in data modeling, mapping, and solution design.

Key Responsibilities

Design end-to-end data solutions for migration waves and net new use cases, covering ingestion, transformation, and consumption layers.

Develop conceptual, logical, and physical data models aligned to business and analytical needs.

Define source to target mappings and transformation logic, including handling of data types, nulls, defaults, SCDs, and business rules.

Make hands on Google Cloud Platform service design decisions across BigQuery, Dataflow, Cloud Composer, Dataform, and Cloud Storage, balancing performance, cost, and security.

Design dimensional and analytics ready data models (star schemas, fact/dimension structures).

Apply security and least privilege access principles at the dataset and domain level.

Partner with Tech Leads and Data Engineers to guide implementation and review builds against design intent.

Work with Product Managers, Business Analysts, and SMEs to translate requirements into executable solution designs and data product definitions.

Collaborate with QA/QE teams to ensure quality is designed in including validation hooks, reconciliation strategy, and data quality expectations.

Align with platform architecture teams to adopt standards, surface gaps, and contribute reusable patterns.

Lead solution design reviews and document key decisions, tradeoffs, and rationale.

Contribute to AI/GenAI enablement where it strengthens solution outcomes (metadata driven workflows, AI ready data products, agentic patterns).

Operate within Agile delivery models (Scrum/Kanban) using tools such as Jira and Confluence.

Required Qualifications

7+ years of progressive experience in data engineering and solution architecture on enterprise data platforms.

Strong, hands on experience with Google Cloud Platform data services: BigQuery, Dataflow, Cloud Composer, Dataform, Cloud Storage.

Expertise across the full data lifecycle: modeling, mapping, transformation design, and data product architecture.

Strong foundation in dimensional modeling, star schemas, and analytics ready structures.

Advanced SQL skills for designing and reasoning about complex transformations on large datasets.

Working knowledge of Google Cloud Platform security and access design (IAM, least privilege, dataset/domain level access).

Demonstrated ability to operate across architecture and implementation defining designs, guiding engineers, and reviewing builds.

Strong communication skills with the ability to explain design decisions to technical and non technical stakeholders.

Bachelor s degree in a related field or equivalent experience.

Preferred Qualifications

Experience with platform modernization or EDW to Google Cloud Platform migration programs.

Experience in retail, consumer, or omni-channel data domains (customer, product, inventory, orders, pricing, loyalty).

Familiarity with semantic layer concepts, data catalog/metadata platforms, and governance workflows.

Exposure to LLM enabled or agentic patterns for AI ready data products.

Working proficiency in Python for prototyping or pipeline support.

Google Cloud Platform certifications (Professional Data Engineer or Professional Cloud Architect).

Team & Culture Fit

Pragmatic problem solver who balances speed vs. durability and innovation vs. standardization.

Collaborative and outcome driven works closely with engineering, product, BA, and quality teams.

Strong ownership mindset identifies gaps, proposes solutions, and drives alignment.

Comfortable with ambiguity and multi wave delivery across multiple pipelines.

Clear, concise communicator who can tailor messaging to engineers and executives.