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Titan Master Data Analyst - Back Office
- Dallas, Texas, United States
- Dallas, Texas, United States
Über
The compensation range for this full‑time position applies to candidates located within the United States. Our salary ranges are determined by reviewing roles of similar responsibility and level. Within the salary range, individual pay is determined by several factors including performance, knowledge, job‑related skills, experience, and relevant education or training. Schneider Electric also offers a comprehensive benefits package to support our employees, inclusive of medical (with member reward points), dental, vision, and basic life insurance, Benefit Bucks (credits to apply towards your benefits) flexible work arrangements, paid family leaves, 401(k) + match, well‑being and recognition (including service anniversary) programs, 12 holidays per year, 15 days of paid time off per year (pro‑rated in the first year of employment based on start date), opportunity to purchase company stock (eligibility depends on start date), and military leave benefits.
The Data Analyst – Digital Transformation plays a critical role in Schneider Electric’s S/4HANA deployment across manufacturing plants, ensuring all operational, supply chain, maintenance, and financial master data is accurately prepared, validated, migrated, and governed to enable a smooth cutover and stable post‑go‑live operations. Working closely with functional domains such as Manufacturing, Plant Maintenance, Planning/Procurement, Logistics/Warehousing, and Finance/Costing, this role translates business requirements into clean, compliant, migration‑ready data. Success in this position requires strong analytical skills, exceptional attention to detail, and the ability to work independently in a fast‑paced, high‑impact deployment environment.
Key Responsibilities
Collaborate with business and technical teams in an agile environment to identify critical data objects and define business rules supporting accurate data migration and lifecycle processes.
Prepare, cleanse, transform, and validate master data across functional domains including Manufacturing (PP), Procurement, Planning/MRP, Plant Maintenance (PM), Warehouse/Logistics, Quality (QU), and Finance/Costing.
Execute Upload Data Sheets (UDS), support mock loads, delta loads, and contribute to final cutover activities for S/4HANA deployments.
Troubleshoot master data issues, collaborate with cross‑functional SMEs, and resolve defects promptly.
Analyze, monitor, and improve data quality utilizing Excel, structured validation rules, and data governance practices.
Communicate risks, dependencies, timelines, and blockers to stakeholders and ensure proactive follow‑up.
Develop, maintain, and enhance data templates, documentation, SOPs, and tools to support continuous improvement and automation.
Own the creation, testing (positive & negative), and validation of data migration templates ensuring readiness for SAP ECC/S/4HANA uploads.
Partner closely with business users across global teams to support evolving data requirements and lifecycle management activities.
Contribute to accuracy, stability, and readiness of data for S/4HANA plant deployments to ensure smooth production, maintenance, inventory, procurement, and costing operations.
Mandatory Skills
Strong understanding of end‑to‑end manufacturing processes (logistics, procurement, planning, finance, quality).
5+ years of hands‑on Master Data experience with expertise in SAP master data models.
Familiarity with SAP ECC 6.0 and/or SAP S/4HANA master data structures.
Highly organized with strong attention to detail and accuracy in managing large datasets.
Advanced Excel proficiency (VLOOKUP/XLOOKUP, INDEX/MATCH, Pivot Tables, filters, complex formulas; macros a plus).
Comfortable working with data queries such as SQL.
Strong collaboration skills with the ability to work across technical/business teams and global time zones.
Clear communication skills with the ability to troubleshoot and resolve data issues.
Ability to work independently in a fast‑paced, deadline‑driven environment.
Analytical and proactive approach to data quality improvement.
Required Qualifications
3+ years of experience in at least one functional domain: Manufacturing, Planning & Procurement, Warehouse/Logistics, Plant Maintenance, Quality, or Finance/Costing.
Hands‑on experience working with ERP Master Data in SAP (S/4HANA strongly preferred; ECC experience acceptable).
Demonstrated experience in data cleansing, validation, migration, and data governance.
Strong communication and documentation skills; able to partner with cross‑functional SMEs and plant teams.
Ability to work autonomously with high initiative and minimal supervision.
Proven track record delivering high‑quality, accurate data for deployments or production environments.
Schneider Electric aspires to be the most inclusive and caring company in the world by providing equitable opportunities to everyone, everywhere. We mirror the diversity of the communities in which we operate, and inclusion is one of our core values. We believe our differences make us stronger as a company and as individuals and we are committed to championing inclusivity in everything we do.
At Schneider Electric, we uphold the highest standards of ethics and compliance, and we believe that trust is a foundational value. Our Trust Charter is our Code of Conduct and demonstrates our commitment to ethics, safety, sustainability, quality and cybersecurity, underpinning every aspect of our business and our willingness to behave and respond respectfully and in good faith to all our stakeholders. You can find out more about our Trust Charter here.
Schneider Electric is an Equal Opportunity Employer. It is our policy to provide equal employment and advancement opportunities in the areas of recruiting, hiring, training, transferring, and promoting all qualified individuals regardless of race, religion, color, gender, disability, national origin, ancestry, age, military status, sexual orientation, marital status or any other legally protected characteristic or conduct.
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Sprachkenntnisse
- English
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