Principal Product Solution Architect

We are seeking a visionary Principal Product Solutions Architect to lead the technical design, configuration patterns, and system orchestration for our next-generation Enterprise Financial Close, Reconciliation, and Anomaly Detection product.Our product is built on top of an advanced, internal, metadata-driven low-code platform featuring a highly interactive, spreadsheet like user interface. This is a specialized product application and data modeling architecture role. Your core mandate is to translate intricate financial compliance logic into a scalable, high-performance product application layer, utilizing an internal engine that abstracts out transformations to natively run on Datalakes. You will architect the application patterns that enable a fast-moving engineering organization of a large team of developers to build concurrently while scaling to process hundreds of millions of transaction rows for global Fortune 500 enterprises.

Not Required: Infrastructure, CI/CD, DevOps, security/authentication, raw ERP data ingestion pipelines, and the standalone machine learning engines are completely managed by dedicated horizontal engineering teams.

Key Responsibilities

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Metadata-Driven Application Design: Architect the semantic data layer, defining how standard and complex custom objects interact within an enterprise-wide low-code data catalog. Ensure flexible configurations seamlessly support varied multinational financial structures out of the box.

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Performance Engineering: Own the approaches to best column-level transformation formulas. Ensure that complex data reconciliation mappings defined by users in an abstract UI adhere to highly efficient, parallelized, and cost-effective Snowflake SQL paths that avoid performance degradation or runaway cloud compute expenses during the critical month-end close window.

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Cross-Team Technical Orchestration: Act as the primary technical ambassador and contract negotiator for the product unit. Collaborate directly with adjacent engineering teams to define robust, production-grade API contracts for ERP Data Ingestion, UI Widgets, and the AI/Rules anomaly detection engine.

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Configuration Governance at Scale: Establish software development lifecycle (SDLC) best practices tailored for a low-code metadata environment. Define patterns for version control, component modularity, testing, and dependency management to enable a large engineering organization to build simultaneously without conflict or regressions.