Principal – Enterprise Data Strategy, Data Quality Assurance & Governance


April 22, 2021

Do what you love. Love what you do.

At Workday, we help the world’s largest organizations adapt to what’s next by bringing finance, HR, and planning into a single enterprise cloud. We work hard, and we’re serious about what we do. But we like to have fun, too. We put people first, celebrate diversity, drive innovation, and do good in the communities where we live and work.
Job Description
Working as part of the data governance and management team, you lead enterprise data governance and quality management initiatives to build the Information Governance strategy. You are a critical leader in laying the foundation for enterprise data policies, standards, and optimized systems/processes to leverage data as an asset for Workday’s growing business. In this role as an internal data strategy consultant, you will develop DQ assurance framework and engagement model, maintain DQ assurance workstream, drive prioritization, interface with business stakeholders and technology partners to guide diagnostic analytics and technical solutioning. This role will primarily interface with Sales and Finance teams and deliver DQ assurance, data catalog and data health scorecard, as critical components of information governance at the enterprise level.
  • Develop data management strategy to build trust in information and capabilities to leverage data as strategic asset to fuel growth
  • Product Owner for end to end lifecycle of data for data governance, MDM and data operations for one more more business function
  • Own data quality framework and data management policy creation by partnering with business partners, with focus on Sales and Finance teams
  • Identify, prioritize and maintain DQ assurance workstream through Information Governance Council
  • Own Information Governance Council agenda and run council meetings, ready to represent data quality cases and present recommended standards, policies and business processes to resolve quality issues
  • Interface with business stakeholders and technology partners to guide diagnostic analytics and technical solutioning of data challenges
  • Own and manage the entire data life cycle for business functions
  • Project manage DQ case management with cross-functional teams, set agenda, invite appropriate members to participate, brainstorm diagnostic analysis and assign to business analytics team, and converge diverse POVs on data quality issues and solutions into practical solutions to ensure consistency and accuracy on data
  • Summarize key findings and make solutions recommendations to data owners who own the business processes that impacts the data
  • Define methods for measuring and monitoring data quality and policy adherence
  • Evaluate tools to enable data quality framework and recommend customizations
  • Establish DQ KPIs and benchmarks
  • Define and manage CRUD policy. Engage with cross functional team and stakeholders to influence and drive decision making process.
  • Own and drive end to end process documentation
  • Conduct deep data profiling and pattern recognition

  • B.S., M.S. in Informatics, Computer Science, Statistics, Business, or related area/ Or equivalent work experience
  • 10+ years of related and progressive experience in Data Quality management and Data Governance, related fields
  • Experience in drafting and managing data policies, business data processes, data catalogs, and business glossaries
  • Knowledge of Sales and Finance operations for SaaS business preferred
  • Experience driving data governance including: project/program management and change management
  • Knowledge of master data initiatives and core data management strategies and best practices
  • Knowledge of business processes, technical practices impacting data quality is important
  • Experience with metadata and reference data software packages/architecture
  • Experience with enterprise source systems and of systems that consume master and reference data, including CRM, ERP and Data Warehouse/Business Intelligence
  • Familiarity with data processing and data warehouse / big data environments tools/languages, such as SQL, R, Python, etc
  • Experience with Data Quality and Governance tools (Alteryx, Waterline, Collibra, Apache Atlas, Informatica Data Quality)
  • Experience with advanced and statistical analysis/ modeling