Live opening · Posted 6 hours ago

Product Owner

Infosys · Hyderabad, Telangana, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 6 hours ago
CompanyInfosys
LocationHyderabad, Telangana, India (On-site)
Work modeNo
SkillsAWS, Azure, Power BI
SourceLinkedin
ListedPosted 6 hours ago

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About the role

Description supplied by the original job listing.

Master's in CS / Engineering / Statistics / IT / Information Systems
10+ years of total experience; 5–7 yrs Data Product Management, agile, full product lifecycles(discovery → delivery)
You have strong experience in the FMCG/ Retail Data & Analytics Domain
You have proven Track record of Implementing Data products related to Product Lifecycle Management (Ingredients, Semi Finished Goods, BOM, Packaging Items) and experience in integrating sources with standard MDM principles.
You have ability to demonstrate a mix of technical skills and business processes knowledge and proven experience in rolling out a data product in multiple markets. Essential to have experience in data catalogue documentation and manage the product use throughout all the stages of the product lifecycle.
You have strong experience working with Data Architects, Ingestion, Data scientists and visualization teams in an agile framework. Expert knowledge and demonstrated abilities to lead squads and tribes with ability to define user stories and prioritizing backlog in accordance with the Senior Product Owner’s vision of the product.
You have strong ability to connect and federate distinct stakeholders in a complex organization, managing stakeholders from Global, Local, Business and IT colleagues.
You are experienced implementing modern data strategies and solutions using cloud technologies (Azure, AWS, Google), Informatica Cloud, Databricks, Power BI or similar tools.
You have capability to express complex data concepts into lay language for stakeholder management
CYBELE Deployment
Own the successful deployment of CYBELE PLM across regions, categories, and manufacturing sites, ensuring alignment with the global process m[KS2.1][SK2.2]odel and business objectives.
Act as the primary IT representative for data deployment activities, driving scope decisions, deployment readiness, risk management, and stakeholder alignment throughout the programme lifecycle. Data Factory Management
Lead Data Factory activities covering data scoping, profiling, cleansing, enrichment, validation, and migration readiness to support successful CYBELE deployments.
Govern delivery priorities, resource allocation, execution plans, and performance metrics across Data Factory teams, deployment waves, and external partners.
Drive continuous improvement of data quality, automation, and migration methodologies, leveraging lessons learned to scale delivery across future deployment waves. Support & Hypercare
Own post go-live support and hypercare activities, ensuring rapid issue resolution, business continuity, and seamless transition into business-as-usual operations.
Coordinate cross-functional support teams, IT partners, and business stakeholders to manage defects, prioritize remediation, and monitor deployment KPIs. Data Migration
Define and oversee end-to-end data migration strategy, ensuring accurate, complete, and compliant transfer of product, specification, and master data into CYBELE.
Drive data mapping, cleansing, digitization, validation, and quality assurance activities across structured and unstructured data sources. PLM Data Product Ownership
Own the vision, strategy, and roadmap for PLM data products and associated data assets.
Partner with R&I business stakeholders to translate business needs into prioritized data capabilities and enhancements.
Define and manage data product backlogs, requirements, and value delivery metrics.
Ensure data quality, governance, metadata, and business ownership are embedded across the PLM landscape.
Drive harmonization and standardization of PLM data across regions, functions, and deployment waves.
Oversee the lifecycle of PLM data assets, including enhancements, support, compliance, and continuous improvement.
Collaborate with IT&D Product SMEs, Data Leads, and Digital/Data Factory teams to deliver scalable and sustainable data solutions.

Work arrangement
No

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