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Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformInformaticaPythonServiceNowSQLTableau
About the role
Key responsibilities & impact- Lead the design, integration and execution of our Data strategy rooted in Enterprise DG principles and Data Management capabilities (e.g. dg policy, business/technical metadata CDEs, data lineage, data integration &, interoperability).
- Partner with DG teams to translate business requirement rules into technical specifications for solutioning AI-powered automation, validation, anomaly detection, continuous monitoring & remediation integrating DQ with ServiceNow, Enterprise DQ dashboards and DG Catalog Platform Tools.
- Architect and deploy AI/ML models to automate end-to-end DQ checks (e.g., technical/operational and business rules) across retail business domain functions: finance, inventory, pricing, promotions, assortment, vendor transaction records working with best-in-class DQ and DG Tooling.
- Develop Python-based scripts and metadata enrichment pipelines integrated with governance tooling (e.g., data catalog, DQ dashboards, quality scoring systems).
- Operationalize DQ rule sets tied to critical domains including Retail Product Lifecycle Management, Financial Planning & Analysis, Customer Journeys, and Omnichannel Commerce.
- Deliver visually rich and actionable insights through Power BI/Tableau dashboards tailored to executive, merchandising, and finance teams.
- Facilitate collaboration between DG stewards, domain SMEs, and technology teams to ensure consistent interpretation and enforcement of DQ rules & policies.
- Monitor KPIs that measure DQ impact on business processes and forecast accuracy.
Requirements
What you’ll need- Bachelor’s or Master’s degree in Computer Science, Data Analytics, Business Intelligence, or related field
- 5+ years in Lead Data Quality roles, preferably within Retail, CPG, or B2C eCommerce environments
- Expertise with best-in-class DG Tools (Atlan, Collibra, Monte Carlo, Informatica DQ)
- Experience with Data Governance industry Platform Tools (Collibra, Atlan, Alation) & Data Management Frameworks with ServiceNow DQ workflow integration
- Advanced proficiency in Python building scripts for dq automation integration, and metadata enrichment
- Experience using AI/ML for retail intelligence, predictive modeling, and operational automation
- Mastery of data visualization tools (Power BI, Tableau, Miro) with a flair for insight storytelling
- Proficiency in SQL, relational databases, and cloud-native data warehouses (Azure, GCP, AWS)
- Strong understanding of Retail Product Lifecycle Management (PLM) and Finance Performance Metrics (e.g., FP&A, Company Planning, GL), business and technical metadata (CDE)s for implementing DQ Controls.
Benefits
Comp & perks- Health insurance
- Professional development
ATS Keywords
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Hard Skills & Tools
PythonAI/MLData Quality automationData GovernanceData Management FrameworksSQLData VisualizationMetadata enrichmentPredictive modelingOperational automation
Soft Skills
CollaborationInsight storytellingLeadershipCommunicationProblem-solvingAnalytical thinkingOrganizational skillsFacilitationAdaptabilityStrategic thinking