Job Description

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Location : Pune/Indore/Hyderabad/Bangalore/Ahmedabad
Mode: Hybrid
Contract Duration: 1 year (can be extendable)
SkillSet & Responsibilities-

• Support shaping and executing the manufacturing, quality and IoT product data assets strategy to accelerate the Consumer Health digital transformation and drive financial and strategic outcomes.

• Run hands-on data sourcing, harmonization, and curation for manufacturing, quality and IoT data on a global level.

• Together with the Manager for IoT & Smart Factory Data, support running process changes in alignment with the relevant functions, to ensure data quality from creation. For this, leverage advanced analytics, intelligent automation, data science, and other cutting-edge technologies.

• Communicate data requirements to data providers and monitor the compliance to these requirements.

• Partner with the global and regional manufacturing and quality teams, data management, and other function and operations teams to implement data standards.

• Perform quantitative and qualitative analysis of data to drive business growth.

• Review the existing data quality, identify gaps and recommend improvement measures to data providers.

• Execute data management governance. Monitor data standards and business processes that support data quality.

• Support a diverse and inclusive team culture, where different viewpoints are visibly encouraged and supported.

Related to JIRA & Confluence:
Project Tracking and Reporting in JIRA: Utilize JIRA to manage and track data analysis projects, ensuring that tasks are clearly defined, prioritized, and assigned. This includes
Knowledge Management and Documentation in Confluence: Develop and maintain comprehensive documentation, create and update project wikis, share reports, and ensure that all relevant stakeholders have access to up-to-date information.
Related to Knowledge graphs:
1. passionate about designing, developing and optimizing knowledge graphs
2. stay up-to-date with industry trends and advancements in the knowledge graph space
or
ensure data governance and implement data management best practices in the knowledge graph environment
source and transform data into the knowledge graph in a scalable and efficient manner using ETL solutions
supporting the strategic development, as well as coordination and organization around all aspects of the knowledge graph
capture architecture requirements and design scalable knowledge graph infrastructures