Sr. Technical Project Manager

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Requirements:

• Bachelor's degree in computer science/engineering, mathematics, economics, or related field.
• 5+ years experience managing complex technical projects ideally in the data and analytics space.
• Experience managing project budgets and timelines.
• Proficiency in Jira and software development methodologies (agile/scrum).
• Proficiency in Microsoft Office PowerPoint, Excel, and SharePoint.
• Understanding of cloud-native architectures, services, and data analytics patterns.
• Understanding of Business Intelligence and Analytics tools (Tableau, Power BI) and ability to analyze data sets.
• Strong communication skills to present to high-level executives and engage with product owners and development teams.
• Experience assessing and managing vendor relationships for data and analytics initiatives.

Responsibilities:

• Lead the end-to-end delivery of data and analytics projects within the portfolio, ensuring they are completed on time, on budget, within scope, and to the highest quality standards.
• Drive a culture of excellence in project execution.
• Collaborate closely with senior leadership to define and execute the strategic vision for data and analytics within the organization.
• Translate this vision into actionable plans and projects.
• Engage with internal stakeholders across various business units to understand their data and analytics needs.
• Translate these requirements into actionable project plans and prioritize delivery efforts accordingly.
• Ensure that our data and analytics solutions are technically sound, scalable, and aligned with industry best practices.
• Stay up to date with latest technologies and trends in data management and analytics.
• Establish and track key performance metrics for data and analytics projects, regularly reporting progress to senior leadership and making data-driven recommendations for improvements.
• Analyze and synthesize data from multiple sources ensuring alignment with long range plan and budget goals.
• Implement process improvements: identify operational gaps and implement them to optimize processes, reducing costs and improving efficiency.