Data Architect We are seeking an experienced Data Architect to define and evolve enterprise data architecture and design scalable, secure, high-performing data solutions aligned with business strategy. The role will shape target-state architecture, platform capabilities, data patterns, and modernization roadmaps across ingestion, storage, transformation, governance, analytics, and AI consumption. The ideal candidate combines deep architecture expertise with strong understanding of Finance, Sales, or Operations. This role partners with Product, Engineering, Analytics, AI, and business leaders to establish architecture direction, guide solution design, and ensure the data platform remains reusable, interoperable, governed, and future-ready.
Key Responsibilities:- Design Scalable Data Solutions
- Build and Evolve the Data Platform
- Drive Data Strategy and Collaboration
- Ensure Standards and Innovation
Required Skills & Experience:
12+ years of experience in Data Engineering, Data Architecture, Data Warehousing, or Enterprise Architecture. Proven experience defining and implementing enterprise-scale data architectures and cloud data platforms. Experience leading modernization initiatives and architecture roadmaps across complex data ecosystems. Strong record of designing solutions that support analytics, operational reporting, AI/ML, and business growth. Mandatory Skills: Enterprise and solution data architecture Snowflake-aligned platform architecture Conceptual, logical, and physical data modeling Data warehouse, lakehouse, and data-lake architecture Batch, streaming, real-time, API, and event-driven integration patterns Cloud architecture on Azure, AWS, or GCP Metadata, lineage, data-quality, privacy, and governance architecture Performance, resilience, availability, disaster recovery, and cost optimization Architecture standards, reference patterns, design reviews, and technology evaluation Functional / Domain Experience: Experience in at least one of the following domains: Finance — FP&A, revenue analysis, budgeting, forecasting, or P&L analytics Sales — sales operations, pipeline analytics, CRM insights, or revenue growth Operations — process optimization, workforce planning, productivity, or operational analytics Executive stakeholder management Technical leadership and strategic roadmap development Ability to connect business strategy with target-state data capabilities and investment priorities
Technical Skills:
Snowflake Data Cloud architecture and solution design Enterprise data warehousing, lakehouse, data mesh, and data-product architectures Dimensional modeling, Data Vault, and semantic data models ELT/ETL, CDC, streaming, and data-pipeline architecture Snowpark using Python or SQL and Snowflake Cortex AI Performance engineering, workload management, and FinOps principles Data sharing, Snowflake Marketplace, and Native Applications GenAI, LLMs, RAG, vector search, and AI-ready platform architecture APIs, event-driven architecture, microservices integration, CI/CD, infrastructure as code, and Git
