Associate Data Analyst

Workday is a leading AI platform for managing people, money, and agents, and they are seeking an Associate Data Analyst to collaborate with cross-functional teams. In this role, you will analyze complex business problems using data and translate those needs into well-designed, reusable data assets.

Responsibilities:

• Partner with cross‑functional stakeholders (e.g., product, sales, finance, HR, operations) to identify, define, and clarify business problems and opportunities, and translate these into clear data product requirements
• Analyze datasets from Workday and other systems to identify trends, patterns, and drivers that inform the design of scalable data products and shared metrics
• Design and iterate on reusable data assets (e.g., curated datasets, semantic layers, standardized dashboards) that can support multiple teams and use cases, rather than one‑off analyses
• Write and optimize SQL queries to extract, join, and validate data from relational sources, ensuring performance, reliability, and alignment with our data models
• Use data analysis tools and visualization platforms to build intuitive, self‑service reporting and analytics experiences that empower stakeholders to answer their own questions where appropriate
• Apply strong Analytical Thinking and Problem Analysis to break down complex, ambiguous questions into structured problems with clear hypotheses, methods, and success criteria
• Demonstrate Business Acumen by understanding how different functions operate, how their metrics relate, and how shared data products can create leverage across organizations
• Contribute to Data Governance by helping define and document metrics, data definitions, and usage guidelines for data products, and by raising and tracking data quality issues with appropriate owners
• Collaborate with analytics engineers, data engineers, and other analysts to align on data models, pipelines, and technical standards that support reliable data products
• Participate in and sometimes facilitate cross‑functional design reviews, stakeholder workshops, and feedback sessions to refine data products and ensure they meet real user needs
• Support testing and validation of new or updated data products, including sanity checks, reconciliation with source systems, and tracking issues through to resolution
• Contribute to documentation, playbooks, and knowledge‑sharing so that data products are well understood and easy to adopt across teams