Company Name:-
Veritas Technologies

Job Location:-
Pune, Maharashtra

Job Summary:-
About VERITAS
Veritas solves what no one else can.

With an industry-leading product portfolio, we offer proven, modern, and integrated technology that brings together availability , protection , and insights .

Our Veritas Enterprise Data Services Platform addresses current and future data issues end-to-end – keeping mission-critical workloads highly available, protecting data everywhere, and providing insights to optimize costs and maintain regulatory readiness.

Veritas supports 500+ data sources, 150+ storage targets, 50+ clouds, and any deployment model imaginable.

We serve 99% of the Fortune 100, 90% of the Fortune 500, and are the market leader in Software-defined Storage, Data Protection, and Archiving.

Veritas Customer Success is responsible for ensuring that Veritas’ customers are successfully exceeding the value of their investment in Veritas solutions and coordinating the company focus on the end-to-end customer relationship.

Customer Success includes customer support and care, professional and business critical services, and renewal sales.

Remediate data quality issues submitted to the Intake Portal by members of different business units across multiple systems, this is inclusive of break/fixes, enhancements, and data clean-up
Provide data corrections and updates in multiple Customer Success systems to drive data integrity
Collect, organize and analyze large data sets leveraging, but not limited to, VEMS, OSvC & Oracle ERP, ADR
Drive data mining, auditing and automation initiatives for the team
Ensure that the data needed for the optimal customer experience (both internal and external) are available in a timely manner through maintenance, creation, and archiving.

This includes account, contact, entitlement, ADR and product data.

Integrate corporate- and product-level architecture principles and goals into team’s project work, by providing use cases, requirements and implementation strategies.

Help execute the Data Quality roadmap and strategy to develop and implement data quality and data governance across multiple lines of business.

Drive a culture of quality, technical curiosity, continuous improvement, and evidence-based decision making in the organization.

Develop and participate in UAT testing of

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