Senior MDM Product Data Analyst

Everpure (NYSE: P) has evolved from storage pioneer to data platform closing fiscal 2026 with $3.7 billion in revenue its first billion-dollar quarter and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers AI labs the AI hardware supply chain data platform providers and the broader AI ecosystem.

This type of workwork that changes the worldis what the tech industry was founded on. So if youre ready to seize the endless opportunities and leave your mark come join us.

THE ROLE

We are seeking an experienced MDM Product Data Analyst to support the management quality
governance and transformation of product master data across enterprise systems. The role will work
closely with Product Business Engineering Data Governance and technical teams to analyze complex
product data define and validate data quality rules support MDM onboarding and migration and drive
resolution of data issues. The ideal candidate combines strong product data and MDM expertise with
advanced SQL analytical problem-solving and practical use of AI/GenAI to improve data analysis and
delivery.

WHAT YOULL DO
Analyze manage and reconcile product master data across multiple source systems MDM platforms
and downstream applications.
Leverage AI/GenAI tools to accelerate data profiling analysis data quality rule development
documentation issue investigation and root-cause analysis.
Translate business and product requirements into clear data requirements attribute definitions
validation rules and analytical specifications.
Perform detailed data profiling to identify quality issues gaps inconsistencies anomalies duplicates
and data integrity risks across product attributes and relationships.
Define document implement and validate data quality rules covering completeness accuracy
validity consistency uniqueness and business-rule compliance.
Develop source-to-target analysis and reconciliation approaches to validate data movement
mappings transformations and synchronization across systems.
Work with Product and Business stakeholders to understand product structures SKUs
product/component relationships configurations classifications and product lifecycle requirements.
Analyze and resolve complex product data issues including incorrect attribute values missing data
duplicate records mapping issues hierarchy discrepancies and configuration gaps.
Support MDM data onboarding enrichment cleansing migration and transformation activities
including data preparation and validation.
Develop data validation logic and partner with technical teams on implementation testing and
automation of DQ rules.
Participate in UAT data certification defect triage root-cause analysis and issue resolution; ensure
defects are clearly documented and tracked through closure.
Create data correction files and coordinate with technical teams to implement and validate required
fixes.
Support development and maintenance of product data dictionaries attribute definitions business
rules reference data and data governance documentation.
Partner with Data Governance teams to define data ownership standards allowed values reference
data and validation requirements.
Monitor and report data quality metrics trends defects and remediation progress providing clear
status updates and recommendations to stakeholders.
Identify recurring data quality issues and recommend process data model integration or system
improvements to prevent recurrence.
Contribute to large-scale MDM implementation migration and transformation programs and support
continuous improvement of product data processes.
Required Skills & Experience
8 years of relevant experience in Data Analytics Master Data Management Product Data
Management and/or Data Quality.
Strong hands-on experience working with Product Master Data and Product Catalog data.
Strong understanding of SKU structures product hierarchies attributes product/component
relationships configurations lifecycle and classification.
Strong SQL skills for data extraction profiling reconciliation validation and investigative analysis.

Hands-on experience with data quality frameworks DQ rule development data profiling and issue
remediation.
Experience performing source-to-target data analysis reconciliation mapping validation and
integration analysis.
Strong understanding of data governance concepts including data ownership data standards
business rules reference data and allowed values.
Hands-on experience working with Reltio as an MDM platform.
Experience with CPQ Product Catalog Salesforce Zuora NetSuite or CRM systems.
Experience working with hardware software SaaS or subscription-based product data.
Experience with product configuration and product/component relationships.
Experience working with Snowflake.
Familiarity with automated data quality tools such as Ataccama.
Practical experience using AI/GenAI tools to improve data analysis DQ rule development
documentation and root-cause analysis.
Experience supporting UAT data certification defect triage and cross-functional issue resolution.
Experience supporting large-scale MDM implementation migration or transformation programs.
Strong analytical structured problem-solving and attention-to-detail skills.
Excellent written and verbal communication skills with the ability to present data findings risks and
recommendations to both technical and business stakeholders.
Ability to work effectively across Product Engineering Data Governance Business and technical
teams.
Experience analyzing complex product catalogs with high volumes of SKUs and attribute
combinations.
Experience developing reusable data validation and reconciliation approaches for recurring data
quality checks.
Experience identifying opportunities to automate manual data analysis validation and remediation
activities using AI/GenAI or scripting.
Understanding of enterprise product data integrations and downstream consumption patterns.
Experience working in Agile delivery environments and participating in requirements grooming
backlog refinement and data-focused delivery planning.
Key Competencies
Product Data & MDM expertise
Data Quality & Governance
SQL & Data Analysis
Source-to-Target Reconciliation
Product Structures SKUs & Configurations
AI/GenAI-enabled Data Analysis
Problem Solving & Root-Cause Analysis
Stakeholder Management & Communication

WHAT YOU BRING

8 years of relevant experience in Data Analytics Master Data Management Product Data
Management and/or Data Quality.
Strong hands-on experience working with Product Master Data and Product Catalog data.
Strong understanding of SKU structures product hierarchies attributes product/component
relationships configurations lifecycle and classification.
Strong SQL skills for data extraction profiling reconciliation validation and investigative analysis.

Hands-on experience with data quality frameworks DQ rule development data profiling and issue
remediation.
Experience performing source-to-target data analysis reconciliation mapping validation and
integration analysis.
Strong understanding of data governance concepts including data ownership data standards
business rules reference data and allowed values.
Hands-on experience working with Reltio as an MDM platform.
Experience with CPQ Product Catalog Salesforce Zuora NetSuite or CRM systems.
Experience working with hardware software SaaS or subscription-based product data.
Experience with product configuration and product/component relationships.
Experience working with Snowflake.
Familiarity with automated data quality tools such as Ataccama.
Practical experience using AI/GenAI tools to improve data analysis DQ rule development
documentation and root-cause analysis.
Experience supporting UAT data certification defect triage and cross-functional issue resolution.
Experience supporting large-scale MDM implementation migration or transformation programs.
Strong analytical structured problem-solving and attention-to-detail skills.
Excellent written and verbal communication skills with the ability to present data findings risks and
recommendations to both technical and business stakeholders.
Ability to work effectively across Product Engineering Data Governance Business and technical
teams.
Experience analyzing complex product catalogs with high volumes of SKUs and attribute
combinations.
Experience developing reusable data validation and reconciliation approaches for recurring data
quality checks.
Experience identifying opportunities to automate manual data analysis validation and remediation
activities using AI/GenAI or scripting.
Understanding of enterprise product data integrations and downstream consumption patterns.
Experience working in Agile delivery environments and participating in requirements grooming
backlog refinement and data-focused delivery planning.

Key Competencies
Product Data & MDM expertise
Data Quality & Governance
SQL & Data Analysis
Source-to-Target Reconciliation
Product Structures SKUs & Configurations
AI/GenAI-enabled Data Analysis
Problem Solving & Root-Cause Analysis
Stakeholder Management & Communication

#LI-REMOTE #LI-ONSITE

WHAT YOU CAN EXPECT FROM US:

• Innovation: We celebrate those who think critically like a challenge and aspire to be trailblazers.
• Growth: We give you the space and support to grow along with us and to contribute to something meaningful. We have been named Fortunes Best Workplaces in Technology Fortunes Best Workplaces in the Bay Area and certified as a Great Place to Work!
• Team: We build each other up and set aside ego for the greater good.

And because we understand the value of bringing your full and best self to work we offer a variety of perks to manage a healthy balance including flexible time off wellness resources and company-sponsored team events. Check out for more information.

ACCOMMODATIONS AND ACCESSIBILITY:

Candidates with disabilities may request accommodations for all aspects of our hiring process. For more on this contact us at if youre invited to an interview.

OUR COMMITMENT TO A STRONG AND INCLUSIVE TEAM:

Were forging a future where everyone finds their rightful place and where every voice matters. Where uniqueness isnt just accepted but embraced. Thats why we are committed to fostering the growth and development of every person cultivating a sense of community through our Employee Resource Groups and advocating for inclusive leadership.

Everpure is proud to be an equal opportunity employer. We do not discriminate based upon race religion color national origin sex (including pregnancy childbirth or related medical conditions) sexual orientation gender gender identity gender expression transgender status sexual stereotypes age status as a protected veteran status as an individual with a disability or any other characteristic legally protected by the laws of the jurisdiction in which you are being considered for hire.

Join us and bring your best.

Bring your bold.

Pure and simple.