Data Product Manager
Role: Data Product AnalystLocation: Jersey City, NJ/ Wilmington. DE, (5 days office)Duration: ContractThe Data Product Analyst owns data as a product across its lifecycle from source systems through data platforms (Databricks), into AI/ML pipelines, and finally to production and UAT. This role bridges business, data engineering, and AI teams, ensuring data products are well‑defined, governed, high‑quality, and fit for analytics and automation use cases.This is not a BI‑only role and not a data engineer role.It is a product‑oriented data role operating in an AI‑enabled enterprise environment. Product & Analysis Skills3+ years’ experience in Data Product Analyst, Product Analyst, or Product‑centric Data rolesStrong understanding of the product development lifecycleProven ability to translate business needs into epics, features, and user storiesExperience working in Agile / Scrum environments Data & Platform SkillsStrong SQL proficiency for:Data validationTestingAd‑hoc analysisHands‑on understanding of:Data pipelinesLarge‑scale datasetsWorking knowledge of modern data platforms:DatabricksSnowflakeCloud data ecosystems Governance & Compliance SkillsExperience with:Data onboardingMetadata managementData cataloging and lineageFamiliarity with control‑heavy / regulated environmentsUnderstanding of entitlements, data quality tooling, and governance workflows Nice‑to‑Have SkillsExposure to AI/ML‑enabled data productsExperience validating AI outputs from a business and data perspectiveDomain experience in enterprise operations, HR/Talent, or financial servicesExperience working with enterprise ERP or operational datasetsPython programming knowledge experience Core Responsibilities 1. Data Product Ownership & DiscoveryPartner with Product Managers to identify and define data product opportunities aligned to customer and business needsConduct user discovery, stakeholder interviews, and journey mapping to identify data gaps, pain points, and opportunitiesDefine product vision, scope, and success metrics for assigned data products 2. Requirements & Agile DeliveryTranslate business needs into:Product requirementsEpics, features, and user storiesClear acceptance criteriaOwn and manage a prioritized data product backlogSupport sprint planning, reviews, and UAT in Agile/Scrum teams 3. Data Platform & AI EnablementCollaborate with Data Engineering to onboard new data sources from internal systems (e.g., ERP / SCM platforms)Work with AI/ML teams to:Define data inputs and featuresValidate post‑processing logic and outputsEnsure data products meet analytics, reporting, and automation requirements 4. Data Quality, Governance & LifecycleDefine and enforce:Data quality rulesValidation checksSLAs across processing and AI layersEstablish and maintain:Data catalogBusiness glossaryMetadata and lineageEnsure compliance with enterprise governance standards in regulated environments 5. Measurement & Continuous ImprovementTrack and analyze product metrics including:TimeCostQualityAdoption and usageDrive continuous improvement through stakeholder feedback and usage insightsThank youPraveenpraveen.s@themesoft.com