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Mid-level data role in metro with strong global brand and generalist technical requirements.
Strong HR/Workday and MDM domain requirements reduce industry transferability.
Explicit 3–5 years plus mandatory Python, SQL, Snowflake and data governance skills.
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Own investigation and root cause analysis of global Skills and Job Architecture data quality issues impacting payroll, reporting, AI models, and integrations.
Design, build, and maintain automated data quality pipelines and monitoring dashboards using Python, SQL, and Snowflake to ensure AI-ready HR data standards.
Lead data remediation activities including automated correction scripts and partner with global process owners and Workday teams to implement structural fixes and governance improvements.
Degree in Information Systems, Data Engineering, Computer Science, Data Management, or related field.
3–5 years of experience in data engineering, data quality, data governance, or related analytical/technical roles.
Hands-on experience with Python scripting, SQL, Snowflake, ELT/ETL pipelines, and data quality monitoring tools (e.g., Informatica CDGC).
Experience with HR data domains (employee records, skills profiles, payroll) and data remediation processes including EIB loads.
Experienced in global, matrixed organizations operating at the intersection of HR data, governance, and technology platforms, especially Workday HCM and Skills Cloud.
Strong technical operator capable of developing data pipelines, automation, and dashboards to ensure operational excellence and AI readiness.
Familiar with AI/ML data pipeline requirements, with proven ability to translate business data quality needs into technical solutions and measurable outcomes.