SE Intel Data Quality Stream Leader

SE Intel Data Quality Stream Leader

Schneider Digital Data & Performance is responsible for fostering Group strategy execution by leveraging data as an enabler for performance management. The SE Intel Data Quality Stream Leader role defines, implements, and leads end‑to‑end data quality governance for the SE Intel application, ensuring that data consumed across the organization is trusted, timely, and fit for purpose.

Responsibilities

Data Quality Strategy

• Translate high‑level data governance rules into concrete use cases for Reusable Data Objects (RDOs) and KPIs consumed in SE Intel.
• Define and own the end‑to‑end data quality framework across SE Intel.
• Partner with cross‑functional data domains and data offices to govern the quality of the enterprise data, aligning with commercial roadmaps and business value.
• Establish and maintain a single source of truth for 10,000+ business users, including Business Pulse and ExCom.
• Act as the internal expert on data governance rules and data quality best practices, showcasing to stakeholders.

Development

• Design and build data quality monitoring rules across all data sources, applying the company’s data quality framework to SE Intel’s key performance drivers.
• Create and maintain data quality checks and dashboards per data source, prioritizing with product owners and data offices.
• Drive backlog prioritization, contributing to sprint planning and Agile ceremonies.
• Ensure alignment with data quality guidelines and the company’s data maturity model.
• Ensure excellent user experience by following SE Intel guidelines on design, security, performance, database architecture, and communication.
• Support the integration of AI‑ready data quality standards as SE Intel evolves toward GenAI and conversational analytics capabilities.

Run, Root Cause Analysis & Continuous Improvement

• Ensure data quality on monthly disclosures and new releases; own critical data objects including Net Orders, Invoiced Sales, Opportunities, and the enterprise offer portfolio end‑to‑end.
• Act as level‑2 support for tickets raised in Service Now for Data Objects in scope; triage, assign, and track issues.
• Root Cause Analysis (RCA): Lead structured investigations into data quality failures across SE Intel’s data pipeline.
• Preventive Action & Issue Closure: Ensure every resolved issue is followed through with a documented preventive action.
• Recurring Issue Pattern Analysis: Continuously analyze the DQ issue backlog to detect patterns, clusters, and systemic trends.
• Support secure data extraction for ad‑hoc management needs, enforcing data security protocols.

Team & Stakeholder Management

• Directly manage a cross‑functional team of Data Engineers, Analysts, and Tableau/Visualization Developers.
• Lead cross‑team collaboration with stream leaders, business product owners, technical product owners, and data offices.
• Influence and convince stakeholders at all levels, including ExCom, on data quality strategy and roadmap prioritization.
• Lead change management and communication initiatives to drive adoption of DQ standards and processes.
• Participate in working groups addressing SE Intel‑specific transformation challenges and improvement projects.

Qualifications

• Master’s degree in a technical field (Data Science, Computer Science, Engineering, or equivalent).
• Prior experience in data quality, data governance, or data engineering; demonstrated expertise in DQ frameworks and end‑to‑end implementation.
• Advanced SQL skills.
• Strong plus: SAP SD data model and process knowledge, Salesforce, Tableau, Informatica Cloud, AWS/Redshift architecture.
• Demonstrated experience managing or leading cross‑functional teams.
• Project management experience with Agile methodology.
• Strong leadership and communication skills; proven ability to engage top management (ExCom level).
• Experience working with global teams across different functions and geographies.
• Data governance certification a strong plus (e.g., DCAM Certified, EDM Council or equivalent).
• Exposure to GenAI/AI product development, particularly in the context of data quality for AI pipelines and Text‑to‑SQL environments.

Location

Barcelona, Spain; Bangalore, India

Grade 8