Job Summary:
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.
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Technical Domain Liaison: Work closely with a team of Product Managers to dissect sophisticated accounting workflows (such as intercompany reconciliations and ledger-to-subledger matching) and translate them into robust, reproducible platform configurations.
Skills and experience needed
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Platform-Native Architectural Experience: A proven track record of designing large-scale, metadata-driven systems. Deep familiarity with expanding or building heavy business applications on top of highly structured platforms (e.g., Salesforce Lightning/Apex, ServiceNow, Guidewire, SAP NetWeaver, or highly complex internal PaaS frameworks).
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Expertise in Domain-Driven Design (DDD): Superior capability to transform fluid business logic and accounting rules into immutable, structured entity relationships and declarative constraints.
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Systems Orchestration Mindset: Exceptional capacity to design complex application state workflows, cross-system dependency mappings, and cleanly isolated service contracts without managing raw infrastructure.
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Outstanding Technical Communication: A proven history of writing clear, comprehensive RFCs and technical documentation, with the executive presence to negotiate architectural priorities across multi-functional core platform teams.
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Prior experience working in the financial technology space (Corporate Accounting, Auditing, Fintech SaaS, or ERP customizations).
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Experience designing software that complies with strict enterprise audit requirements (SOX compliance, data lineage, SOC 2).
What You Will NOT Need to Do
Because we have dedicated underlying infrastructure and core engine teams, your background does not need to emphasize:
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Core cloud-native infrastructure administration (Kubernetes, Docker, Service Meshes, Terraform).
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Low-level systems programming or building Java/Go microservices from scratch.
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Writing raw Machine Learning training loops or building native ETL ingestion adapters.