Principal Product Manager – Enterprise Systems Data

Principal Product Manager – Enterprise Systems Data

Bellevue, WA, USA

Corporate Systems Engineering builds and operates the software platforms, integrations, and automations that power Smartsheet’s core business functions across Finance, Sales/GTM, and People & Culture. Our team owns mission‑critical systems and workflows that enable how the company hires, sells, bills, pays, reports, and scales. We operate at the intersection of software engineering, enterprise platforms, and business‑critical data, treating internal systems with the same rigor, reliability, and product mindset as customer‑facing software.

Corporate Systems Product Management focuses on the internal platforms that power how Smartsheet operates - including Finance, People, Sales operations, integrations, and internal automation. Product Managers in this team steward system roadmaps, business workflows, and long‑term platform evolution across these domains.

As Principal Product Manager – Enterprise Systems Data
, you will own the strategy and evolution of how Corporate Systems data is structured, governed, and consumed. This includes defining system‑of‑record strategies, improving data quality and observability, and enabling consistent, trusted data flows across platforms such as Salesforce, Net Suite, Workday, product systems, and the data lake. You will operate at the intersection of Engineering, Business Systems, Data Engineering, and Analytics to ensure that data is not only available, but accurate, consistent, and usable across the enterprise.

This role is responsible for driving clarity in data ownership, reducing fragmentation, and enabling scalable reporting, analytics, and AI use cases.

This full‑time position reports to the Director of Corporate Systems Product Management and can be located in our Bellevue, WA office, or you may work remotely from anywhere in the US where Smartsheet is a registered employer.

• Own the product vision, roadmap, and prioritization for data platforms and governance across Corporate Systems
• Define and drive the strategy for system‑of‑record and source‑of‑truth across enterprise platforms (e.g., Salesforce vs Net Suite vs product systems)
• Partner with Engineering, Data Engineering, and Analytics teams to improve data quality, consistency, and availability across systems
• Lead initiatives to standardize data definitions, models, and contracts across Finance, Sales, and People domains
• Identify and reduce fragmentation caused by duplicate pipelines, shadow reporting, and inconsistent data sources
• Drive adoption of data cataloging and governance tooling (e.g., Atlan) to improve visibility, lineage, and ownership
• Partner with teams to implement data observability solutions (e.g., Monte Carlo) to proactively detect and resolve data issues
• Define and enforce data contracts between upstream systems (product, billing, CRM) and downstream consumers (Snowflake, BI tools, AI systems)
• Improve reliability and timeliness of data pipelines supporting critical processes such as bookings, ARR reporting, and financial reconciliation
• Partner with business stakeholders (Finance, Rev Ops, BI) to translate reporting challenges into systemic data improvements rather than manual workarounds
• Establish metrics to track data quality, pipeline reliability, and adoption of governed data sources
• Communicate trade‑offs and roadmap decisions across technical and business stakeholders
• Support governance, lifecycle planning, and change management for data‑related system changes

• Bachelor’s degree in Business, Information Systems, Computer Science, or a related field — or equivalent practical experience. Advanced degree is a plus but not required
• 8+ years of experience in Product Management, Business Systems, Data Platforms, or similar roles
• Strong experience working with enterprise systems and their data models (e.g., Salesforce, Net Suite, Workday, product platforms)
• Familiarity with data platforms such as Snowflake, Databricks, or similar data lakes/warehouses
• Experience working with data pipelines, ETL/ELT processes, and system integrations
• Strong understanding of data governance, data quality, and data modeling concepts
• Experien…