Senior Data Solution Architect

We are seeking a hands-on Senior Data Solution Architect to design and validate a production-grade data foundation that supports analytics and AI-agent consumption. You will shape data models, integration patterns, and Big. Query standards while partnering with engineering to deliver governed, reliable datasets.

Responsibilities

Define target data architecture for cost, usage, resource, contract, finance, metadata, and operational datasets Design conceptual, logical, and physical data models for Big. Query analytical workloads Create source-to-target mappings, transformation rules, data contracts, lineage documentation, and business definitions Establish canonical entities, domain models, semantic datasets, and reusable dimensions for analytics and agent use cases Define data layer standards across raw, standardized, curated, and analytics-ready zones with clear ownership boundaries Design integration patterns for APIs, files, databases, event streams, and semi-structured sources Set Big.

Query standards for partitioning, clustering, materialized views, schema conventions, and query optimization Review SQL, schemas, and pipeline designs to improve scalability, maintainability, performance, and cost efficiency Partner with engineering to define ingestion, transformation, enrichment, reconciliation, and data-quality patterns Establish governance standards for lineage, ownership, access control, retention, classification, freshness, and quality Coordinate architecture and code reviews and provide technical direction across the data domain Requirements Data architecture experience (3+ years) designing analytical platforms and multi-source integrations on Google Cloud Platform Technical leadership experience guiding senior engineers and aligning stakeholders on data architecture decisions Project delivery experience producing architecture artifacts, source-to-target mappings, and proof-of-concept validations Advanced SQL skills with hands-on Big.

Query experience for modeling, optimization, and cost-efficient query design Strong data modeling skills across conceptual, logical, physical, dimensional, and canonical/domain models Hands-on Python skills for data services, transformations, proofs of concept, or API integrations Strong communication skills to translate requirements into clear, actionable specifications Upper-Intermediate English proficiency (B2) for daily collaboration and documentation Nice to have Google Cloud Big.

Query expertise with enterprise-scale optimization and administration Python proficiency for building data tooling or integration services Data Governance experience with catalogs, lineage, and access control standards Data Model expertise for semantic layers and domain-oriented datasets Stakeholder Management experience in cross-functional, architecture-driven programs