Partner Business Intelligence Analyst

Workday•Frisco, TX

1d•$93,900 - $166,900•Hybrid

About The Position

This is a backend-focused analytics engineering role that builds and owns the data foundation for Global Partner Operations. You will design the data models, pipelines, and governance standards that make partner data trustworthy, connected, and reusable across the organization — supporting analytics and reporting for our three partner tracks: Partner Innovation, Partner Sales, and Partner Services. Each track asks different questions of the same ecosystem. Partner Innovation needs visibility into co-innovation activity, solution development, and marketplace and certification outcomes. Partner Sales needs a clear, defensible view of partner-sourced and partner-influenced pipeline, co-sell and resell motions, and route-to-market coverage. Partner Services needs to understand delivery capacity, certified skills, deployment health, and services partner performance. Your job is to build a unified partner data model that serves all three without forcing each team into its own silo of one-off extracts. This is a builder role. Expect to spend the majority of your time in SQL, in the warehouse, and in the semantic layer — designing durable models rather than assembling slides. You will be the technical owner of how partner data is structured, governed, and consumed.

Requirements

5+ years of experience in sales analytics, partner or channel analytics, revenue operations, analytics engineering, or data engineering.
5+ years of hands-on, advanced SQL experience — window functions, CTEs, complex joins, incremental logic, and query performance tuning.
3+ years of experience building and maintaining data models in a cloud data warehouse, with direct Snowflake experience.
Demonstrated experience with dimensional data modeling and data warehouse design (star/snowflake schemas, fact and dimension design, grain definition, slowly changing dimensions).
Demonstrated experience implementing data governance practices — data quality controls, documentation, lineage, access management, or metric certification.
Bachelor's degree in a quantitative, technical, or business field, or equivalent practical experience.

Nice To Haves

Experience developing dashboards, semantic models, or governed datasets in a modern BI platform; Sigma experience strongly preferred.
Experience with dbt or a comparable transformation framework, including modular model design, testing, and documentation.
Proficiency in Python for data engineering tasks: pipeline development, API integrations, automation, and data validation.
Experience with Salesforce or another CRM data model, and with PRM or partner portal data structures.
Understanding of partner ecosystem concepts: partner tiering and program compliance, sourced and influenced attribution, co-sell and resell motions, marketplace and solution certification, services delivery and capacity planning.
Familiarity with sales and services metrics such as bookings, ACV/ARR, pipeline coverage, utilization, and deployment health.
Exposure to data observability or data quality tooling (Monte Carlo, Great Expectations, dbt tests, or similar).
Experience supporting a global organization across multiple regions, currencies, and fiscal calendars.
Familiarity with data controls and reporting standards in a public company environment.
Excellent written communication — you can explain a modeling decision to an engineer and a data discrepancy to an operations leader in the same afternoon.

Responsibilities

Design, build, and maintain dimensional data models in Snowflake that unify partner data across the Partner Innovation, Partner Sales, and Partner Services tracks, including a shared partner master, hierarchy, tiering, and program taxonomy.
Develop and optimize ELT pipelines integrating data from CRM, PRM, partner portal, marketplace, certification and enablement platforms, services delivery systems, and internal Workday systems.
Own the certified semantic layer and Sigma models that Partner Operations managers, track leaders, and cross-functional stakeholders build from — including metric definitions, row-level security, and workbook governance.
Translate partner program logic and track-specific business rules into version-controlled, testable transformation code, with documentation clear enough that any number can be traced back to its source.
Establish and enforce data governance across the partner data domain: naming standards, data dictionaries, lineage, ownership, access controls, and data quality monitoring with defined thresholds and alerting.
Build the reporting foundation for partner attribution — sourced, influenced, and co-sell motions — so that pipeline and bookings analysis is consistent across regions and tracks.
Model partner capacity and capability data — certifications, skills, practice size, delivery footprint — to support Partner Services planning and Partner Innovation solution coverage.
Partner with Partner Operations, Sales Operations, Finance, Enablement, and Partner Program teams to turn ambiguous requirements into durable data architecture instead of recurring manual pulls.
Build reconciliation and validation tooling that supports operating reviews, QBRs, and internal audit or data certification requests.
Improve warehouse performance and cost efficiency through query tuning, clustering strategy, incremental model design, and thoughtful workload management.
Assess the data and system implications of proposed partner program or track changes before launch, and plan the model changes required to support them.
Serve as a technical mentor for less experienced analysts on SQL craft, modeling patterns, and code review standards.