Project Manager (With Data Governance background)

Qualifications:

*Having expertise in data governance, telecom domain is mandatory*

- 12 + years of experience
1. Data Management Expertise: Proficiency in data architecture, data modeling, and data quality assurance is essential.
2. Project Management: Strong project management skills are vital for planning, executing, and monitoring data projects.
3. Technical Proficiency: Familiarity with database systems, ETL (Extract, Transform, Load) processes, and data analytics tools.
4. Communication: Effective communication is necessary to liaise between technical and non-technical teams.
5. Problem-Solving: The ability to troubleshoot issues and find innovative solutions is crucial.
6.Data Governance Knowledge: Understanding data governance principles and compliance regulations is important.
7. Leadership: Leading cross-functional teams and driving collaboration is a significant aspect of the role.

Job Description:

Participate in the implementation of the strategy, solution, design, build and operations for Data Governance program. Develop comprehensive Project plan outlining the scope, objectives, timelines, resources along with scope and risk management plan Devise Plan and oversee data governance processes within customer env for the data platforms Participate in the Implementation, evolve, and promote adoption and use of standard metadata in coordination with customer data stewards, architects, and developers Identify Potential risks and challenges related to the project and develop strategies to mitigate them Provide Leadership and guidance to the project team and collaborate with stakeholders Ensure that security and privacy are foundational in designing and building out data strategies. Evaluate and recommend technologies and tools to implement data governance strategy, including DBMs, data mastering tools, data integration tools, analytic tools, etc. Bring experience with different data use cases and design data models that meet various needs: customer facing analytics, internal advanced analytics, and internal reporting. Be familiar with different design and modeling approaches for those different use cases. Stay abreast of information management trends and standards, master data management, data services, self-service business intelligence, metadata management, data quality, and data governance.