Architect 2, Data

Role overview

Design and guide data architecture that makes organizational data reliable, governed, discoverable, and ready for analytics and AI-enabled applications. You’ll establish shared standards and models, improve data flows across cloud platforms, and work with engineering, product, security, analytics, and governance teams to support product development and trusted self-service use.

Responsibilities - Define reusable data products, semantic models, architecture patterns, contracts, and schema standards. - Lead data modeling from requirements through implementation, including documentation and design decisions for transactional and analytical systems. - Set approaches for metadata, lineage, cataloging, observability, quality, privacy, access control, and AI data governance. - Improve ELT/ETL pipelines, transformation models, and semantic layers for accuracy, performance, and reliability. - Assess and recommend data technologies, and lead proof-of-concept work for new architecture approaches. - Coordinate with architecture and engineering leaders to advance a long-term data vision.

Requirements - 10+ years in data architecture, data engineering, or analytics engineering. - Expert Snowflake experience, including security controls, integrations, semantic views, and performance and cost optimization. - Expert dbt experience, including incremental models, custom materializations, and testing strategy. - Strong background designing data architectures, models, governance practices, and frameworks. - Familiarity with Medallion and Lambda patterns, OLTP modeling, and dimensional analytics models. - Experience with data modeling tools such as Erwin, ER Studio, or equivalents, and with SQL Server.

Nice to have - Exposure to Sigma, Acceldata, Collibra, or related governance and observability tools. - Experience with CosmosDB or MongoDB.