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 work—work that changes the world—is what the tech industry was founded on. So, if you're 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 YOU'LL 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 Fortune's Best Workplaces in Technology™, Fortune's 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 http://benefits.everpuredata.com/ 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 [email protected] if you’re invited to an interview.
OUR COMMITMENT TO A STRONG AND INCLUSIVE TEAM:
We’re forging a future where everyone finds their rightful place and where every voice matters. Where uniqueness isn’t just accepted but embraced. That’s 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.
Skills Required
- 8+ years of relevant experience in data analytics, master data management, product data management, and/or data quality
- Hands-on experience with product master data and product catalog data
- Understanding of SKU structures, product hierarchies, attributes, product/component relationships, configurations, lifecycle, and classification
- Strong SQL skills for extraction, profiling, reconciliation, validation, and investigative analysis
- Experience with data quality frameworks, rule development, profiling, and issue remediation
- Experience with source-to-target analysis, reconciliation, mapping validation, and integration analysis
- Understanding of data governance, ownership, standards, business rules, reference data, and allowed values
- Hands-on experience with Reltio MDM
- Experience with CPQ, Product Catalog, Salesforce, Zuora, NetSuite, or CRM systems
- Experience 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 for data analysis, data quality rules, 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
- Experience analyzing complex product catalogs with high volumes of SKUs and attribute combinations
- Experience developing reusable data validation and reconciliation approaches
- Experience automating data analysis, validation, and remediation using AI/GenAI or scripting
- Experience with Agile delivery environments, requirements grooming, backlog refinement, and data-focused planning
- Strong analytical, structured problem-solving, attention-to-detail, written communication, and verbal communication skills
- Ability to collaborate across Product, Engineering, Data Governance, Business, and technical teams
Everpure Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Everpure and has not been reviewed or approved by Everpure.
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Equity Value & Accessibility — Equity and stock purchase programs are described as meaningful parts of total compensation, with RSUs and an ESPP highlighted as strengths.
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Strong & Reliable Incentives — Sales compensation is structured to support long sales cycles, including policies that pay full commission until the first sale for new or white‑space accounts.
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Healthcare Strength — Health coverage is portrayed as comprehensive, with multiple medical options, fully covered vision, dental PPO choices, mental‑health resources, and company HSA contributions.
Everpure Insights
What We Do
Pure Storage (NYSE:PSTG) helps innovators build a better world with data. Pure's data solutions enable SaaS companies, cloud service providers, and enterprise and public sector customers to deliver real-time, secure data to power their mission-critical production, DevOps, and modern analytics environments in a multi-cloud environment. One of the fastest growing enterprise IT companies in history, Pure Storage enables customers to quickly adopt next-generation technologies, including artificial intelligence and machine learning, to help maximize the value of their data for competitive advantage. And with a Satmetrix-certified NPS customer satisfaction score in the top one percent of B2B companies, Pure's ever-expanding list of customers are among the happiest in the world.
