Analytics Engineer, Workday

• You are an experienced analyst or analytics engineer who is genuinely happiest in the data layer
• You care about whether a model will still make sense in two years, you write SQL other people can read, and you have strong opinions about grain, slowly changing dimensions, and what belongs in a certified metric definition
• You are comfortable serving several stakeholder groups with different definitions of the same word, and you know how to resolve that in the model rather than in a footnote
• 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
• 5+ years of experience building and maintaining data models in a cloud data warehouse, with direct Snowflake experience
• 5+ years demonstrated experience with dimensional data modeling and data warehouse design (star/snowflake schemas, fact and dimension design, grain definition, slowly changing dimensions)
• 5+ years experience developing dashboards, semantic models, or governed datasets in a modern BI platform; Sigma experience strongly preferred
• 5+ years demonstrated experience implementing data governance practices — data quality controls, documentation, lineage, access management, or metric certification

Desirable

• The Global Partner Operations organization is passionate about developing partnerships that accelerate innovation and growth with Industry differentiation, expanded reach and customer success
• This is an outstanding opportunity to be part of the team that is driving a rapid and global change of paradigm, to embrace a modern ecosystem and implement a unified and global partner strategy with local flavor, with cross-functional engagement in programs, systems, processes and people
• The team's mission is to deliver winning partner engagements focused on time, scale and route to market, aligned to our operational goals and core values
• Build and own the data foundation for Global Partner Operations — designing the data models, pipelines, and governance standards that make partner data trustworthy and reusable across Partner Innovation, Partner Sales, and Partner Services
• You'll create a unified partner data model that supports each track's distinct needs (co-innovation and marketplace outcomes; partner-sourced pipeline and co-sell/resell motions; delivery capacity and services performance) without fragmenting into one-off extracts
• This is a hands-on builder role: expect to spend most of your time in SQL, the warehouse, and the semantic layer, serving as the technical owner of how partner data is structured, governed, and consumed
• 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